wiseodd Goto Github PK

asdl

ASDL: Automatic Second-order Differentiation Library for PyTorch

bayesian_ood_training

cnn-levelset

Source code for Kristiadi and Pranowo, 2017's "Deep Convolutional Level Set Method for Image Segmentation"

compound-density-networks

Implementation of: Kristiadi, Agustinus, and Asja Fischer. "Predictive Uncertainty Quantification with Compound Density Networks." (2019).

controlled-text-generation

Reproducing Hu, et. al., ICML 2017's "Toward Controlled Generation of Text"

cuda-pso

Comparison between CUDA and CPU for PSO using 3-dimensional Levy function as test case

curvlinops

scipy linear operators for the Hessian, Fisher/GGN, and more in PyTorch

fast-neural-style

pytorch implementation of fast-neural-style

generative-models

Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

higher_order_invariance

Code for "Accelerating Natural Gradient with Higher-Order Invariance"

hipsternet

All the hipster things in Neural Net in a single repo

kickstart.nvim

A launch point for your personal nvim configuration

lapeft-bayesopt

Discrete Bayesian optimization with LLMs, PEFT finetuning methods, and the Laplace approximation.

laplace-bayesopt

Laplace approximated BNN surrogate for BoTorch

laplace-redux

Laplace Redux -- Effortless Bayesian Deep Learning

last_layer_laplace

Last-layer Laplace approximation code examples

lula

Companion code for the paper "Learnable Uncertainty under Laplace Approximations" (UAI 2021).

ma-inf-4222-nlp-lab

MA-INF 4222: NLP Lab (University of Bonn)

mcmc

Collection of Monte Carlo (MC) and Markov Chain Monte Carlo (MCMC) algorithms applied on simple examples.

molskill

Extracting medicinal chemistry intuition via preference machine learning

nanogpt

The simplest, fastest repository for training/finetuning medium-sized GPTs.

natural-gradients

Collection of algorithms for approximating Fisher Information Matrix for Natural Gradient (and second order method in general)

olympus

Olympus: a benchmarking framework for noisy optimization and experiment planning

phd_thesis_template

priornetworks

probabilistic-models

Collection of probabilistic models and inference algorithms

pyhessian

PyHessian is a Pytorch library for second-order based analysis and training of Neural Networks

pytorch-classification

Classification with PyTorch.

rescal.py

Python module to compute the RESCAL tensor factorization

rgpr

Companion code for the paper "An Infinite-Feature Extension for Bayesian ReLU Nets That Fixes Their Asymptotic Overconfidence" (NeurIPS 2021)