jianvora

jianvora's Stars

• pytorch-labs/gpt-fast

  Simple and efficient pytorch-native transformer text generation in <1000 LOC of python.

  Language:Python5.6k512

• snap-stanford/MLAgentBench

  Language:Python24634

• allenai/ScienceWorld

  ScienceWorld is a text-based virtual environment centered around accomplishing tasks from the standardized elementary science curriculum.

  Language:Scala21326

• CompVis/stable-diffusion

  A latent text-to-image diffusion model

  Language:Jupyter Notebook68.2k10.2k

• AndyShih12/mac

  PyTorch implementation for "Training and Inference on Any-Order Autoregressive Models the Right Way", NeurIPS 2022 Oral, TPM 2023 Best Paper Honorable Mention

  Language:Python113

• Div99/IQ-Learn

  (NeurIPS '21 Spotlight) IQ-Learn: Inverse Q-Learning for Imitation

  Language:Python20231

• starry-sky6688/MARL-Algorithms

  Implementations of IQL, QMIX, VDN, COMA, QTRAN, MAVEN, CommNet, DyMA-CL, and G2ANet on SMAC, the decentralised micromanagement scenario of StarCraft II

  Language:Python1.5k283

• kandouss/marlgrid

  Gridworld for MARL experiments

  Language:Python13725

• google/ml-fairness-gym

  Language:Python31280

• eitanrich/gans-n-gmms

  Official implementation of "On GANs and GMMs"

  Language:Python6519

• BayesWatch/nas-without-training

  Code for Neural Architecture Search without Training (ICML 2021)

  Language:Python46063

• skolouri/swgmm

  Sliced Wasserstein Distance for Learning Gaussian Mixture Models

  Language:Jupyter Notebook5814

• joaoantoniocn/AM-SincNet

  The Additive Margin SincNet (AM-SincNet) is a new approach for speaker recognition problems which is based in the neural network architecture SincNet and the additive margin softmax (AM-Softmax) loss function. It uses the architecture of the SincNet, but with an improved AM-Softmax layer.

  Language:Python439

• janson9192/autokws2021

  Language:Shell132

• WannabeSmith/confseq_wor

  Code for confidence sequences for sampling without replacement (NeurIPS, 2020). https://arxiv.org/pdf/2006.04347.pdf

  Language:Jupyter Notebook5

• shahana-ibrahim/joint-probability-estimation

  Language:MATLAB41

• cambridge-mlg/EinsumNetworks

  Language:Python5021

• mhw32/multimodal-vae-public

  A PyTorch implementation of "Multimodal Generative Models for Scalable Weakly-Supervised Learning" (https://arxiv.org/abs/1802.05335)

  Language:Python15436

• iffsid/mmvae

  Multimodal Mixture-of-Experts VAE

  Language:Python19242

• lrjconan/GRAN

  Efficient Graph Generation with Graph Recurrent Attention Networks, Deep Generative Model of Graphs, Graph Neural Networks, NeurIPS 2019

  Language:C++46896

• idea-iitd/graphgen

  GraphGen: A Scalable Approach to Domain-agnostic Labeled Graph Generation

  Language:C++4914

• timbmg/Sentence-VAE

  PyTorch Re-Implementation of "Generating Sentences from a Continuous Space" by Bowman et al 2015 https://arxiv.org/abs/1511.06349

  Language:Python587153