Piyushi-0

Piyushi-0's Stars

• yuxiangw/autodp

  autodp: A flexible and easy-to-use package for differential privacy

  Language:Jupyter Notebook26953

• BorealisAI/private-data-generation

  A toolbox for differentially private data generation

  Language:Python12832

• BorisMuzellec/kernel-SoS-distributions

  Language:Jupyter Notebook3

• nerdslab/latentOT

  Latent optimal transport (LOT) for low rank transport and clustering

  Language:Jupyter Notebook194

• mblondel/smooth-ot

  Python implementation of smooth optimal transport.

  Language:Python5713

• diff-usion/Awesome-Diffusion-Models

  A collection of resources and papers on Diffusion Models

  Language:HTML11.3k952

• psclklnk/currot

  Source Code for the ICML Paper "Curriculum Reinforcement Learning via Constrained Optimal Transport"

  Language:C++111

• locuslab/projected_sinkhorn

  Language:Python8714

• theislab/single-cell-best-practices

  https://www.sc-best-practices.org

  Language:Jupyter Notebook819198

• DingfanChen/GS-WGAN

  Official implementation of "GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators" (NeurIPS 2020)

  Language:Python6821

• nv-tlabs/DP-Sinkhorn_code

  Language:Python113

• laura-rieger/deep-explanation-penalization

  Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" https://arxiv.org/abs/1909.13584

  Language:Jupyter Notebook12814

• google-research/fast-soft-sort

  Fast Differentiable Sorting and Ranking

  Language:Python57848

• sgstepaniants/GULP

  This repository contains the code to replicate the results in the paper: "GULP: a prediction-based metric between representations".

  Language:Jupyter Notebook81

• inria-thoth/cyanure

  Cyanure: An Open-Source Toolbox for Empirical Risk Minimization

  Language:C++6312

• theislab/moscot

  Multi-omic single-cell optimal transport tools

  Language:Python1199

• chingyaoc/InfoOT

  [ICML2023] InfoOT: Information Maximizing Optimal Transport

  Language:Python406

• yzhao062/pyod

  A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques

  Language:Python8.7k1.4k

• facebookresearch/w2ot

  Euclidean Wasserstein-2 optimal transportation

  Language:Python444

• LucasBoTang/Optimal_Classification_Trees

  Three MIP models for optimal classification tree: OCT, binOCT, flowOCT

  Language:Jupyter Notebook5716

• SaitejaUtpala/rieoptax

  Riemannian Optimization Using JAX

  Language:Jupyter Notebook475

• vios-s/DiffAN

  Diffusion Models for Causal Discovery

  Language:Python8313

• tml-epfl/sgd-sparse-features

  SGD with large step sizes learns sparse features [ICML 2023]

  Language:Jupyter Notebook325

• watml/robust-gan

  Training GANs under contamination

  Language:Python21

• fwilliams/scalable-pytorch-sinkhorn

  Language:Python1437

• justkolesov/Wasserstein1Benchmark

  A set of tests for evaluating large-scale algorithms for Wasserstein-1 transport computation (NeurIPS'22).

  Language:Jupyter Notebook201

• Algue-Rythme/OCSDF

  Semi-supervised learning of 1-Lipschitz Signed Distance Functions

  Language:Jupyter Notebook31

• pytorch/rl

  A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

  Language:Python2.5k328

• lorenzo-park/domain-adaptation-pytorch-lightning

  Language:Python8

• jmkuebler/auto-tst

  AutoML Two-Sample Test

  Language:Python191