moellenh

moellenh's Stars

• tqdm/tqdm

  :zap: A Fast, Extensible Progress Bar for Python and CLI

  Language:Python28.7k2089991.4k

• garrettj403/SciencePlots

  Matplotlib styles for scientific plotting

  Language:Python7.1k6195712

• google-deepmind/dm-haiku

  JAX-based neural network library

  Language:Python2.9k37249233

• davda54/sam

  SAM: Sharpness-Aware Minimization (PyTorch)

  Language:Python1.8k1281196

• lezcano/geotorch

  Constrained optimization toolkit for PyTorch

  Language:Python65793634

• google-research/sam

  Language:Python56691872

• ssydasheng/Bayesian_neural_network_papers

  Papers for Bayesian-NN

  31419052

• google-deepmind/kfac-jax

  Second Order Optimization and Curvature Estimation with K-FAC in JAX.

  Language:Python248111722

• SamsungLabs/ASAM

  Implementation of ASAM: Adaptive Sharpness-Aware Minimization for Scale-Invariant Learning of Deep Neural Networks, ICML 2021.

  Language:Python1406514

• ermongroup/sliced_score_matching

  Code for reproducing results in the sliced score matching paper (UAI 2019)

  Language:Python1393322

• ssydasheng/FBNN

  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)

  Language:Python804210

• team-approx-bayes/ivon

  IVON optimizer for neural networks based on variational learning.

  Language:Python52404

• GongXinyuu/sngan.pytorch

  An unofficial Pytorch implementation of SNGAN, achieving IS of 8.21 and FID of 14.21 on CIFAR-10.

  Language:Python462310

• team-approx-bayes/fromp

  Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"

  Language:Python44236

• ppwwyyxx/FRN-on-common-ImageNet-baseline

  Filter Response Normalization tested on better ImageNet baselines.

  Language:Python3550

• hiyouga/AMP-Regularizer

  Code for our paper "Regularizing Neural Networks via Adversarial Model Perturbation", CVPR2021

  Language:Python34348

• team-approx-bayes/bayesian-sam

  Code for "SAM as an Optimal Relaxation of Bayes", ICLR 2023.

  Language:Python23421

• didriknielsen/ds3_abi_exercises

  Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018

  Language:Jupyter Notebook225110

• yzhwang/jax-multi-gpu-resnet50-example

  An example showing how to use jax to train resnet50 on multi-node multi-GPU

  Language:Python20201

• emtiyaz/cvi

  Code for AISTATS 2017 paper on "Conjugate-Computation Variational Inference"

  Language:MATLAB19321

• team-approx-bayes/kpriors

  Code for Knowledge-Adaptation Priors based on the NeurIPS 2021 paper by Khan and Swaroop.

  Language:Python16302

• devansh20la/LPF-SGD

  Language:Jupyter Notebook14337

• EmanuelLaude/compot

  Composite optimization toolbox: python library for fast composite optimization

  Language:Python8100

• team-approx-bayes/memory-perturbation

  Code for "The Memory Perturbation Equation: Understanding Model’s Sensitivity to Data", NeurIPS 2023.

  Language:Python8200

• team-approx-bayes/liegroups

  Code for "The Lie-Group Bayesian Learning Rule", AISTATS 2023.

  Language:Python7301

• team-approx-bayes/ivon-experiments

  Language:Python6100

• rioyokotalab/hpsc-2022

  Language:Shell40028

• ysngshn/ivon-optax

  An Optax-based JAX implementation of the IVON optimizer for large-scale VI training of NNs (ICML'24 spotlight)

  Language:Python4300

• kigo24/AdamB

  Language:Python2100

• ysngshn/ojax

  OJAX is a small extension of JAX to facilitate modular coding.

  Language:Python2100