Yoontae Hwang's Projects
Unofficial Implementation of A uniformly distributed random portfolio(UDRP)
Foundation is a flexible, modular, and composable framework to model socio-economic behaviors and dynamics with both agents and governments. This framework can be used in conjunction with reinforcement learning to learn optimal economic policies,Β as done by the AI Economist (https://www.einstein.ai/the-ai-economist).
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PyTorch implementation of Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy
implementing "recurrent attentive neural processes" to forecast power usage (w. LSTM baseline, MCDropout)
About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), https://arxiv.org/abs/2106.13008
Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.
A curated list of awesome anomaly detection resources
Awesome Incremental Learning
list of papers, code, and other resources
An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites
A curated list of papers & resources linked to open set recognition, out-of-distribution, open set domain adaptation and open world recognition
Only release code of basic framework and "Online Portfolio Selection with Cardinality Constraint and Transaction Costs based on Contextual Bandit" (IJCAI 2020)
Batch-Instance Normalization (BIN)
Code for paper: Block Hankel Tensor ARIMA for Multiple Short Time Series Forecasting (AAAI-20)
Bigcontest code
Kolmogorov-Arnold Networks (KAN) using Chebyshev polynomials instead of B-splines.
Implementation of COCO-LM, Correcting and Contrasting Text Sequences for Language Model Pretraining, in Pytorch
Unofficial Implementation of Consistency Models in pytorch
All in One - Continual Learning
PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)
Code for the paper "Inference via Interpolation: Contrastive Representations Provably Enable Planning and Inference"
Official Implementation of Data-Driven-Portfolio-Optimization
List of papers, code and experiments using deep learning for time series forecasting
This repository stores the implementation of the paper "DETECTING DATA-DRIVEN ROBUST STATISTICAL ARBITRAGE STRATEGIES WITH DEEP NEURAL NETWORKS"
https://arxiv.org/abs/2102.12658
A paper list for Time series modelling, including prediciton and anomaly detection