awesome-archive / summary

summaries of all the papers I read

summaries of papers on deep learning.

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• [Week-1] 15-Oct-2017 - DL history and basics : DBN, AlexNet, VGGNet, GoogLeNet, ResNet, RNN(speech evolution)
• [Week-2] 22-Oct-2017 - DL methods : models, optimization, deep generative model, rnn/seq-to-seq model
• [Week-3] 29-Oct-2017 - DL methods : Neural Turing Machine,Reinforcement-Transfer-One-Shot Deep Learning
• [Week-4] 06-Nov-2017 - DL applications : nlp, object detection, visual tracking, image caption
• [Week-5] 12-Nov-2017 - DL applications : Machine Translation, Robotics, Art, Object Segmentation
• [Week-6] 19-Nov-2017 - recommender systems
• [Week-7] 26-Nov-2017 - ftm : 01/2011 - 12/2014
• [Week-8] 03-Dec-2017 - ftm : 01/2015 - 12/2015
• [Week-9] 10-Dec-2017 - ftm : 01/2016 - 05/2016
• [Week-10] 17-Dec-2017 - ftm : 06/2016 - 12/2016
• [Week-11] 24-Dec-2017 - ftm : 01/2017 - 07/2017
• [Week-12] 31-Dec-2017 - ftm : 08/2017 - 12/2017

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• [Jan-2018]
• [Feb-2018]
• [March-2018]
• [April-2018]
• [May-2018]
• [June-2018]

Articles

• [Jan2March 2018]
• [April2June 2018]
• [2018 so far]
• [2018-Jan-Sep]
• [conferences-2018]

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12/2018

• Theory of Cognitive Relativity: A Promising Paradigm for True AI
• Modeling Theory of Mind for Autonomous Agents with Probabilistic Programs
• Bag of Tricks for Image Classification with Convolutional Neural Networks
• Learning 3D Human Dynamics from Video
• MS-ASL: A Large-Scale Data Set and Benchmark for Understanding American Sign Language
• Designing quantum experiments with a genetic algorithm
• SADA: Semantic Adversarial Diagnostic Attacks for Autonomous Applications
• ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware
• Brief survey of Mobility Analyses based on Mobile Phone Datasets
• Wireless Data Acquisition for Edge Learning: Importance Aware Retransmission
• An Introduction to Deep Reinforcement Learning
• Visual Object Networks: Image Generation with Disentangled 3D Representation
• Project Rosetta: A Childhood Social, Emotional, and Behavioral Developmental Ontology
• Forging new worlds: high-resolution synthetic galaxies with chained generative adversarial networks
• Online Model Distillation for Efficient Video Inference
• Adversarial Vision Challenge
• Recursive Visual Attention in Visual Dialog
• Deep Architectures for Learning Context-dependent Ranking Functions
• Snips Voice Platform: an embedded Spoken Language Understanding system for private-by-design voice interfaces
• e-SNLI: Natural Language Inference with Natural Language Explanations
• Towards High Resolution Video Generation with Progressive Growing of Sliced Wasserstein GANs
• Tube-CNN: Modeling temporal evolution of appearance for object detection in video
• Computer Vision for Autonomous Vehicles
• A Parallel Divide-and-Conquer based Evolutionary Algorithm for Large-scale Optimization
• Sim-to-Real Optimization of Complex Real World Mobile Network with Imperfect Information via Deep Reinforcement Learning from Self-play
• Pseudo-Rehearsal: Achieving Deep Reinforcement Learning without Catastrophic Forgetting
• HAQ: Hardware-Aware Automated Quantization
• Meta-Transfer Learning for Few-Shot Learning
• Security and Privacy Issues in Deep Learning
• DNQ: Dynamic Network Quantization
• Summarizing Videos with Attention
• Exploring galaxy evolution with generative models
• EENMF: An End-to-End Neural Matching Framework for E-Commerce Sponsored Search
• Visual Attention for Behavioral Cloning in Autonomous Driving
• Law and Adversarial Machine Learning
• A Style-Based Generator Architecture for Generative Adversarial Network
• Improving fairness in machine learning systems: What do industry practitioners need?
• Gaussian Process Deep Belief Networks: A Smooth Generative Model of Shape with Uncertainty Propagation
• IRLAS: Inverse Reinforcement Learning for Architecture Search
• Learning to Communicate: A Machine Learning Framework for Heterogeneous Multi-Agent Robotic Systems
• Adversarial Transfer Learning
• Neural Approaches to Conversational AI
• Revisiting Exploration-Conscious Reinforcement Learning
• Deep Face Image Retrieval: a Comparative Study with Dictionary Learning
• TextBugger: Generating Adversarial Text Against Real-world Applications
• A comparison of cluster algorithms as applied to unsupervised surveys
• On-line Adaptative Curriculum Learning for GANs
• Transfer Learning using Representation Learning in Massive Online Open Courses
• DeepProbLog: Neural Probabilistic Logic Programming
• Linking Artificial Intelligence Principles
• Scalable End-to-End Autonomous Vehicle Testing via Rare-event Simulation
• Gaussian Process Deep Belief Networks: A Smooth Generative Model of Shape with Uncertainty Propagation
• Comixify: Transform video into a comics
• Policy Search in Continuous Action Domains: an Overview
• Transfer Learning in Brain-Computer Interfaces with Adversarial Variational Autoencoders
• Bayesian Optimization in AlphaGo
• A Tutorial on Deep Latent Variable Models of Natural Language
• Traceability of Deep Neural Networks
• TechKG: A Large-Scale Chinese Technology-Oriented Knowledge Graph
• Towards Real-Time Accurate Object Detection in Both Images and Videos Based on Dual Refinement
• The Entropy of Artificial Intelligence and a Case Study of AlphaZero from Shannon's Perspective
• Contingency-Aware Exploration in Reinforcement Learning
• Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference
• Latent Dirichlet Allocation in Generative Adversarial Networks
• Quantum Memristors in Quantum Photonics
• A Tutorial on Distance Metric Learning: Mathematical Foundations, Algorithms and Software
• Evolutionary Neural Architecture Search for Image Restoration
• DVC: An End-to-end Deep Video Compression Framework
• Soft Actor-Critic Algorithms and Applications
• Imitation Learning for End to End Vehicle Longitudinal Control with Forward Camera
• End to End Video Segmentation for Driving : Lane Detection For Autonomous Car
• Deep Learning on Graphs: A Survey
• Why Self-Attention? A Targeted Evaluation of Neural Machine Translation Architectures
• Scaling shared model governance via model splitting
• FML: Face Model Learning from Videos
• Generative One-Shot Learning (GOL): A Semi-Parametric Approach to One-Shot Learning in Autonomous Vision
• Machine Learning in Cyber-Security - Problems, Challenges and Data Sets

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11/2018

• Horizon: Facebook's Open Source Applied Reinforcement Learning Platform [code]
• Applications of Deep Learning to Nuclear Fusion Research
• Towards Explainable NLP: A Generative Explanation Framework for Text Classification
• CariGANs: Unpaired Photo-to-Caricature Translation
• Predicting Demographics, Moral Foundations, and Human Values from Digital Behaviors
• Algorithms for screening of Cervical Cancer: A chronological review
• A Survey on Natural Language Processing for Fake News Detection
• The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale
• A Fast Algorithm for Clustering of High Dimensional Feature Vectors
• Toward an AI Physicist for Unsupervised Learning
• You Only Search Once: Single Shot Neural Architecture Search via Direct Sparse Optimization
• Evolutionary Data Measures: Understanding the Difficulty of Text Classification Tasks
• Security for Machine Learning-based Systems: Attacks and Challenges during Training and Inference
• Language GANs Falling Short
• Are Deep Policy Gradient Algorithms Truly Policy Gradient Algorithms?
• Learning from Demonstration in the Wild
• A Survey on Data Collection for Machine Learning: a Big Data - AI Integration Perspective
• Mesh-TensorFlow: Deep Learning for Supercomputers
• ImageNet/ResNet-50 Training in 224 Seconds
• Natural Environment Benchmarks for Reinforcement Learning
• Reward learning from human preferences and demonstrations in Atari ⭐
• Mathematical Analysis of Adversarial Attacks
• Going Deeper with Semantics: Video Activity Interpretation using Semantic Contextualization
• Towards Explainable Deep Learning for Credit Lending: A Case Study
• Preliminary Studies on a Large Face Database
• Effect of data reduction on sequence-to-sequence neural TTS
• Effects of Dataset properties on the training of GANs
• On-line Adaptative Curriculum Learning for GANs
• GPipe: Efficient Training of Giant Neural Networks using Pipeline Parallelism
• Active Inverse Reward Design
• DropFilter: A Novel Regularization Method for Learning Convolutional Neural Networks
• Incentivizing the Dynamic Workforce: Learning Contracts in the Gig-Economy
• ConvS2S-VC: Fully convolutional sequence-to-sequence voice conversion
• An Algorithmic Perspective on Imitation Learning
• DeRPN: Taking a further step toward more general object detection
• Activation Maximization Generative Adversarial Nets
• CADP: A Novel Dataset for CCTV Traffic Camera based Accident Analysis
• Streaming End-to-end Speech Recognition For Mobile Devices
• Economics of Human-AI Ecosystem: Value Bias and Lost Utility in Multi-Dimensional Gaps
• Scalable agent alignment via reward modeling: a research direction ⭐
• Automatic Paper Summary Generation from Visual and Textual Information
• Learned Video Compression
• PydMobileNet: Improved Version of MobileNets with Pyramid Depthwise Separable Convolution
• Image Classification at Supercomputer Scale
• The PyTorch-Kaldi Speech Recognition Toolkit
• Adversarial Autoencoders for Generating 3D Point Clouds
• Large Scale GAN Training for High Fidelity Natural Image Synthesis
• An Introduction to Image Synthesis with Generative Adversarial Nets
• When Conventional machine learning meets neuromorphic engineering: Deep Temporal Networks (DTNets) a machine learning frawmework allowing to operate on Events and Frames and implantable on Tensor Flow Like Hardware
• Improving Natural Language Inference Using External Knowledge in the Science Questions Domain
• On Human Robot Interaction using Multiple Modes
• Guiding Policies with Language via Meta-Learning
• Improving Automatic Source Code Summarization via Deep Reinforcement Learning
• Pitfalls of Graph Neural Network Evaluation
• Emergence of linguistic conventions in multi-agent reinforcement learning
• The Mirage of Action-Dependent Baselines in Reinforcement Learning
• Automated Algorithm Selection on Continuous Black-Box Problems By Combining Exploratory Landscape Analysis and Machine Learning
• The Mafiascum Dataset: A Large Text Corpus for Deception Detection
• Deeper Interpretability of Deep Networks
• High Speed Event-based Face Detection and Tracking in the Blink of an Eye
• Explicit Bias Discovery in Visual Question Answering Models
• Generative Adversarial Network Architectures For Image Synthesis Using Capsule Networks
• Towards Global Explanations for Credit Risk Scoring
• Watermark Retrieval from 3D Printed Objects via Convolutional Neural Networks
• Deep Active Learning with a Neural Architecture Search
• iQIYI-VID: A Large Dataset for Multi-modal Person Identification
• HAQ: Hardware-Aware Automated Quantization
• Artificial Intelligence-Defined 5G Radio Access Networks
• Synetgy: Algorithm-hardware Co-design for ConvNet Accelerators on Embedded FPGAs
• 50 Years of Test (Un)fairness: Lessons for Machine Learning
• European Union regulations on algorithmic decision-making and a "right to explanation"
• Gradient Descent Finds Global Minima of Deep Neural Networks
• GAN Dissection: Visualizing and Understanding Generative Adversarial Networks
• Context-Aware Crowd Counting
• InstaNAS: Instance-aware Neural Architecture Search
• Deep Learning Inference in Facebook Data Centers: Characterization, Performance Optimizations and Hardware Implications
• Machine Learning for Health (ML4H) Workshop at NeurIPS 2018
• Representation Mixing for TTS Synthesis
• Woulda, Coulda, Shoulda: Counterfactually-Guided Policy Search
• Robust Artificial Intelligence and Robust Human Organizations ⭐
• Show, Control and Tell: A Framework for Generating Controllable and Grounded Captions
• MLModelScope: Evaluate and Measure ML Models within AI Pipelines
• From Recognition to Cognition: Visual Commonsense Reasoning
• Interpretable Convolutional Filters with SincNet
• Dataset Distillation
• LSTA: Long Short-Term Attention for Egocentric Action Recognition
• Feature-Fused SSD: Fast Detection for Small Objects
• Deformable ConvNets v2: More Deformable, Better Results
• TimbreTron: A WaveNet(CycleGAN(CQT(Audio))) Pipeline for Musical Timbre Transfer
• A computational perspective of the role of Thalamus in cognition
• Towards Long-Term Memory for Social Robots: Proposing a New Challenge for the RoboCup@Home League
• Automated Algorithm Selection: Survey and Perspectives
• LRW-1000: A Naturally-Distributed Large-Scale Benchmark for Lip Reading in the Wild
• Towards Decentralization of Social Media
• Neuro-memristive Circuits for Edge Computing: A review
• Deep Reinforcement Learning for Autonomous Driving
• Actor-Critic Policy Optimization in Partially Observable Multiagent Environments
• Prioritizing Starting States for Reinforcement Learning
• DLHub: Model and Data Serving for Science
• Towards Identifying and Managing Sources of Uncertainty in AI and Machine Learning Models - An Overview
• Kalman filter demystified: from intuition to probabilistic graphical model to real case in financial markets
• Snap ML: A Hierarchical Framework for Machine Learning
• Face Detection in the Operating Room: Comparison of State-of-the-art Methods and a Self-supervised Approach
• Demonstrating Advantages of Neuromorphic Computation: A Pilot Study
• ShelfNet for Real-time Semantic Segmentation
• Attentive Relational Networks for Mapping Images to Scene Graphs
• ApolloCar3D: A Large 3D Car Instance Understanding Benchmark for Autonomous Driving
• Recurrent Relational Networks
• Fashion-Gen: The Generative Fashion Dataset and Challenge
• A Century Long Commitment to Assessing Artificial Intelligence and its Impact on Society
• Foot Pressure from Video: A Deep Learning Approach to Predict Dynamics from Kinematics
• Measure, Manifold, Learning, and Optimization: A Theory Of Neural Networks
• Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects

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10/2018

• The Profiling Machine: Active Generalization over Knowledge
• AI Benchmark: Running Deep Neural Networks on Android Smartphones
• A deep learning pipeline for product recognition on store shelves
• MyCaffe: A Complete C# Re-Write of Caffe with Reinforcement Learning
• Quantum Artificial Life in an IBM Quantum Computer
• Finding Solutions to Generative Adversarial Privacy
• Towards Fast and Energy-Efficient Binarized Neural Network Inference on FPGA
• Scaling Video Analytics Systems to Large Camera Deployments
• From Soft Classifiers to Hard Decisions: How fair can we be?
• AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias
• Comparison of Reinforcement Learning algorithms applied to the Cart Pole problem
• Auto-Keras: Efficient Neural Architecture Search with Network Morphism
• An Overview on Application of Machine Learning Techniques in Optical Networks
• A Tale of Three Probabilistic Families: Discriminative, Descriptive and Generative Models
• Transfer Metric Learning: Algorithms, Applications and Outlooks
• Secure Deep Learning Engineering: A Software Quality Assurance Perspective
• BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding [code] [code] ⭐
• Is multiagent deep reinforcement learning the answer or the question? A brief survey
• CURIOUS: Intrinsically Motivated Multi-Task, Multi-Goal Reinforcement Learning
• On the Margin Theory of Feedforward Neural Networks
• Private Machine Learning in TensorFlow using Secure Computation
• Applications of Deep Reinforcement Learning in Communications and Networking: A Survey
• Automatic Full Compilation of Julia Programs and ML Models to Cloud TPUs
• Intrinsic Social Motivation via Causal Influence in Multi-Agent RL
• Do Deep Generative Models Know What They Don't Know?
• Neighbourhood Consensus Networks
• The Uncertainty Bellman Equation and Exploration
• Humans are still the best lossy image compressors
• Model-Based Active Exploration
• Reversible Recurrent Neural Networks
• Graph Convolutional Reinforcement Learning for Multi-Agent Cooperation
• Multi-Agent Common Knowledge Reinforcement Learning
• Tackling Sequence to Sequence Mapping Problems with Neural Networks
• Applying Deep Learning To Airbnb Search
• Inverse reinforcement learning for video games
• Fast and accurate object detection in high resolution 4K and 8K video using GPUs
• Towards Efficient Large-Scale Graph Neural Network Computing
• An Exploration of Dropout with RNNs for Natural Language Inference
• Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells
• Memory Replay GANs: learning to generate images from new categories without forgetting
• You May Not Need Attention [code]
• Face Recognition: From Traditional to Deep Learning Methods
• Democratizing Production-Scale Distributed Deep Learning
• Scalable End-to-End Autonomous Vehicle Testing via Rare-event Simulation
• WaveGlow: A Flow-based Generative Network for Speech Synthesis
• Dial2Desc: End-to-end Dialogue Description Generation
• Taking Human out of Learning Applications: A Survey on Automated Machine Learning
• DeepMasterPrints: Generating MasterPrints for Dictionary Attacks via Latent Variable Evolution

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09/2018

• Hamiltonian Descent Methods
• Deep Learning for Generic Object Detection: A Survey
• Unity: A General Platform for Intelligent Agents
• Five lessons from building a deep neural network recommender for marketplaces
• Focus Group on Artificial Intelligence for Health
• Deep Learning in Information Security
• LiveBot: Generating Live Video Comments Based on Visual and Textual Contexts
• IncSQL: Training Incremental Text-to-SQL Parsers with Non-Deterministic Oracles
• Identifying Real Estate Opportunities using Machine Learning
• Deep Learning Towards Mobile Applications
• HappyDB: A Corpus of 100,000 Crowdsourced Happy Moments
• Urban morphology meets deep learning: Exploring urban forms in one million cities, town and villages across the planet
• Graph Convolutional Networks for Text Classification
• Identifying Generalization Properties in Neural Networks
• Towards Deep and Representation Learning for Talent Search at LinkedIn
• Cellular automata as convolutional neural networks
• Realistic Evaluation of Deep Semi-Supervised Learning Algorithms
• AlphaSeq: Sequence Discovery with Deep Reinforcement Learning
• Learning to Interpret Satellite Images Using Wikipedia
• Visual Analytics for Automated Model Discovery
• GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration
• Stakeholders in Explainable AI
• Adversarial Attacks and Defences: A Survey
• Audio-Visual Speech Recognition With A Hybrid CTC/Attention Architecture
• Deep Learning in Mobile and Wireless Networking: A Survey
• Hierarchical Deep Multiagent Reinforcement Learning

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08/2018

• Backprop Evolution
• Sparse and Dense Data with CNNs: Depth Completion and Semantic Segmentation
• Large Scale Language Modeling: Converging on 40GB of Text in Four Hours. paper
• RecoGym: A Reinforcement Learning Environment for the problem of Product Recommendation in Online Advertising
• Neural Arithmetic Logic Units
• CornerNet: Detecting Objects as Paired Keypoints
• A Survey on Deep Transfer Learning
• YOLO3D: End-to-end real-time 3D Oriented Object Bounding Box Detection from LiDAR Point Cloud
• Dialog-context aware end-to-end speech recognition
• An Efficient Deep Reinforcement Learning Model for Urban Traffic Control
• Predicting Expressive Speaking Style From Text In End-To-End Speech Synthesis
• GeneSys: Enabling Continuous Learning through Neural Network Evolution in Hardware
• Application of End-to-End Deep Learning in Wireless Communications Systems
• A Short Note about Kinetics-600
• Smart City Development with Urban Transfer Learning
• Deep Learning Advances on Different 3D Data Representations: A Survey
• Skill Rating for Generative Models. paper
• Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) Network. paper
• Hierarchical Attention: What Really Counts in Various NLP Tasks . paper
• Neural Architecture Search: A Survey. paper
• Rapid Adaptation of Neural Machine Translation to New Languages. paper
• A Survey on Sentiment and Emotion Analysis for Computational Literary Studies. paper
• Video-to-Video Synthesis. arxiv [code]
• CoQA: A Conversational Question Answering Challenge. arxiv
• QuAC : Question Answering in Context. arxiv
• Everybody Dance Now. paper
• Contextual Parameter Generation for Universal Neural Machine Translation. paper
• Fusion++: Volumetric Object-Level SLAM. paper
• Mapping Text to Knowledge Graph Entities using Multi-Sense LSTMs
• FPGA Implementation of Convolutional Neural Networks with Fixed-Point Calculations
• Generalisation in humans and deep neural networks
• All You Need is "Love": Evading Hate-speech Detection

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07/2018

• Troubling Trends in Machine Learning Scholarship
• Machine Learning in High Energy Physics Community White Paper
• Quasi-Dilemmas for Artificial Moral Agents
• Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences
• Comparing Dynamics: Deep Neural Networks versus Glassy Systems
• Financial Trading as a Game: A Deep Reinforcement Learning Approach
• Natural Language Processing for Information Extraction
• Video Summarisation by Classification with Deep Reinforcement Learning
• Generative models on accelerated neuromorphic hardware
• A Survey of Knowledge Representation and Retrieval for Learning in Service Robotics
• Zipf's law in 50 languages: its structural pattern, linguistic interpretation, and cognitive motivation
• JUMPER: Learning When to Make Classification Decisions in Reading
• Universal Word Segmentation: Implementation and Interpretation
• End-to-End Race Driving with Deep Reinforcement Learning
• Taskonomy: Disentangling Task Transfer Learning
• ClariNet: Parallel Wave Generation in End-to-End Text-to-Speech. arxiv
• Hierarchical Multi Task Learning With CTC. arxiv
• When deep learning meets security. arxiv
• Object Detection with Deep Learning: A Review. arxiv
• Towards Automated Deep Learning: Efficient Joint Neural Architecture and Hyperparameter Search. arxiv
• Implementing Neural Turing Machines
• Talk the Walk: Navigating New York City through Grounded Dialogue
• The Lottery Ticket Hypothesis: Finding Small, Trainable Neural Networks
• Learning by Asking Questions
• Deep learning in agriculture: A survey
• Learning Plannable Representations with Causal InfoGAN, ICML / IJCAI / AAMAS 2018 Workshop on(PAL-18).
• Progressive Neural Architecture Search
• Variational Bayesian Reinforcement Learning with Regret Bounds
• Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minutes
• Learning from Delayed Outcomes with Intermediate Observations
• A Survey of the Usages of Deep Learning in Natural Language Processing
• The GAN Landscape: Losses, Architectures, Regularization, and Normalization
• Assessing the Scalability of Biologically-Motivated Deep Learning Algorithms and Architectures
• TherML: Thermodynamics of Machine Learning
• Neural Processes
• GAN Q-learning
• LaneNet: Real-Time Lane Detection Networks for Autonomous Driving
• TextWorld: A Learning Environment for Text-based Games, ICML/IJCAI 2018.
• Perceptrons from Memristors
• Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model
• Large-Scale Visual Speech Recognition

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|| dl-research-groups | dl-frameworks | dl1+dl2 | awesome-dl+roadmap+ml | CB-Insights_AI-100 + AI100_2 | ai-angelList | machine-learning-surveys ||

|| a--rnn | a-deep-vision | a--random-forest | a-computer-vision | a-deep-learning | a-p | d-l-p | drlp | DeepLearningImplementations | drlp2 | dl-papernotes | dl-r | med-appl | very-dl | nn.papers | a-GAN | rl.papers| dnn.med | cuda.programming | caltech.cuda | rtb-papers | deep-learning-nlp-rl-papers | nips2017 | deep_learning_object_detection ||

|| Outline of artificial intelligence | Outline of machine learning | Outline of computer vision | Outline of natural language processing | Outline of robotics | List of datasets for machine learning research| ai applications | UCI.ML.DATASETS | public.datasets | kaggle.datasets | datasets.gh.list | Origin_of_speech ||

|| awesome-nlp | nlp_tasks | DeepNLP-models-Pytorch | oxford.nlp.lectures | stanford.nlp.lectures | nltk.org/book | DL4NLP | cs388.utexas.nlp | nlp-datasets | DL-NLP-Readings | gt-nlp-class ||

[Deep Learning Resources], [DL_libraries_final_Rankings]

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ML/DL Publications

• Arxiv Sanity Preserver
• NIPS
• ICML-17
• AAAI
• CVPapers
• arxiv.ml
• arxiv.cvpr
• arxiv.ai
• arxiv.ne
• arxiv.ro
• arxiv.nc
• hinton
• MILA
• FAIR
• deepmind
• brain team
• andrewng
• yann.lecun,nyu
• manning
• hiit.neuro
• grey.colorado.edu.CCNL
• dbsystem
• nvidia.ml.research
• stanford.vision.lab
• BAIR.people + courses
• CSAIL.people + publications
• SAIL.people + courses
• google.machineIntelligence
• google.MachinePerception
• google.MachineTranslation
• google.NaturalLanguageProcessing
• google.AIResidency
• scholar.cvpr
• scholar.ai
• scholar.gt
• scholar.ro
• shoham
• ai.people
• ml.people
• AAAI.fellows
• UTA.ai
• UTA.dml
• wildml
• rl.gh.p
• nn.gh.p
• openai.requests.research
• psy.ox.ac.uk
• cs.ox.ac.uk
• CV.people
• arXivTimes

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ML/DL Implementations

• deepmind.gh.code
• openai.gh.code
• facebookresearch.gh.code
• frameworks.dl
• ml.python
• deep.nlp.models.pytorch
• rl
• dl.keras.tf
• pytorch.list
• ml.algorithms
• cnn.benchmarks
• pytorch.tut
• pytorch.ex
• torch.start
• dl.tool
• rl.tf
• DCGAN.tf
• ntm.tf
• neural.style
• torch.rnn
• stanford.dl.ex
• deepq.tf
• gan
• ml.hackers.code.r
• bayesian.code.jn
• nn.dl.code
• nn.java
• ml.go
• numenta.gh.code
• tensorflow.gh.code
• neural.doodle.code
• ml.sf.engineering
• tf.models
• DL4NLP
• neural.style.torch
• opencog
• ml.jn.scikit
• bayesian.PyMC3
• tf.ex
• ALE
• aima.py
• deeplearning4j.code
• tflearn.tf
• resnet
• stanford.tf
• top.dl
• tensorlayer.dl.rl
• dl.keras
• dl.docker
• dl.list
• mila.gh.code
• microsoft.gh.code
• CSAILVision.gh.code
• NVIDIA.gh.code
• OpenNMT.code
• Tencent.code
• baidu.code
• stanfordnlp.code
• sar.ml
• sony.code
• ml
• PrincetonVision.code
• commaai.code
• NervanaSystems.code
• pytorch.code
• torch.code
• automl.code
• chainer.code
• dmlc.code
• BVLC.code
• caffe2.code
• aimacode.code
• opencog.code
• opencv.code
• oxford.deepnlp
• USC.ds.code
• gensim.nlp.ir
• scikit.learn.code
• tesseract.code
• ds.ipython
• ml.book
• ccs.video.cources
• eff.tf
• ml.tut
• swift.ai
• tf.book
• ml.mindmaps
• dl
• h2o.ai
• fast.ai
• tf.tut
• tf.tut
• PipelineAI
• PRML
• mlpack
• mit.nlp
• scikit.learn.contrib
• mit.ml.pdf
• ml.py.book
• onnx.code
• aml.sf
• dmml.sf
• prolog.ai
• deep.rl.1
• deep.rl.pytorch
• dl.tut
• dl.trade
• benchm.ml
• dl.java
• dl.tf
• self-car.ai
• dql
• drl.berkeley
• PAIR-code
• fast.ai
• courses.fast.ai
• cs231n.stanford.edu/
• cs224d.stanford.edu/
• oxford-cs-deepnlp-2017
• UFLDL Tutorial 1
• UFLDL Tutorial 2
• dl.NLP (without Magic)|
• dl.p.dn
• dl.bu
• Theano.tut
• nn.Matlab
• cnn.face
• Torch7.tut
• ml.tut.web
• VGG.cnn
• TensorFlow.tut
• TensorFlow.tut+
• TensorFlow.py.n
• Keras.Lasagne.tut
• TensorFlow.LSTM.RNN
• TensorFlow.World
• dl.py
• Grokking.dl
• dl.Search
• Keras.tut
• Pytorch.tut
• Ray Kurzweil
• Andrew Ng
• Geoff Hinton
• Yann LeCun
• Yoshua bengio
• Jeff Hawkins
• Adam Coates
• Adam Coates
• Adam Coates
• Yann LeCun
• Geoffrey Hinton at GoogleTechTalks
• Jeremy Howard at TEDxBrussels
• Andrew Ng in Stanford (2011)
• Chris Manning in Stanford
• Natalie Hammel and Lorraine Yurshansky
• Steve Jurvetson (and panel) at VLAB in Stanford
• Leo Isikdogan at Motorola Mobility HQ
• CS224u: Natural Language Understanding
• Deep Learning – a cookbook view

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ML/DL conferences in 2018

• aideadlin.es
• /r/MachineLearning/
• conference paper templates
• AI Conferences in 2018
• Calendar of Computer Image Analysis, Computer Vision Conferences
• guide2research

Conference Papers:

• JMLR Papers list
• JAIR Paper list
• Google Scholar AI track
• KDD explorations
• CVPR Open Access

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highscalability - to dive in all time favorites list

• [Week-1] 19-Nov-2017
• [Week-2] 26-Nov-2017
• [Week-3] 03-Dec-2017
• [Week-4] 10-Dec-2017
• [Week-5] 17-Dec-2017
• [Week-6] 24-Dec-2017
• [Week-7] 31-Dec-2017
• [startupreadings]
• [awesome-scalability]

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Blockchain	Ethereum	Bitcoin	LTC	Neo	QTUM	UBIQ

• [Week-1] 19-Nov-2017 - decentralized systems(Blockchain)
• [Week-2] 26-Nov-2017 - decentralized systems(Blockchain)
• [Week-3] 03-Dec-2017 - bitcoin content
• [Week-4] 17-Dec-2017 - bitcoin code
• [Week-5] 24-Dec-2017 - ethereum content
• [Week-6] 31-Dec-2017 - ethereum programming + ICO

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|| blockchain-papers | blockchain in action | awesome-blockchain+influencers+whitepapers+cryptocurrency | ICO+Resources||

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Maintainer

Gopala KR / @gopala-kr