scripts for final project

A novel neural network for effective learning of highly impulsive/oscillatory dynamic systems by jointly utilizing low-order derivatives

MuJoCo is a physics engine for detailed, efficient rigid body simulations with contacts. mujoco-py allows using MuJoCo from Python 3.

PyTorch implementation of soft actor critic

A Collection of Variational Autoencoders (VAE) in PyTorch.

Official implementation of "Accelerating Reinforcement Learning with Learned Skill Priors", Pertsch et al., CoRL 2020

Huggingface compatible implementation of RetNet (Retentive Networks, https://arxiv.org/pdf/2307.08621.pdf) including parallel, recurrent, and chunkwise forward.

The GitHub repository for the paper "Informer" accepted by AAAI 2021.

About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), https://arxiv.org/abs/2106.13008

[AAAI-23 Oral] Official implementation of the paper "Are Transformers Effective for Time Series Forecasting?"

Sequence-to-sequence model implementations including RNN, CNN, Attention, and Transformers using PyTorch

Transformer: PyTorch Implementation of "Attention Is All You Need"

RecurDyn automation using Python and ProcessNet

Aggregate multiple tensorboard runs to new summary or csv files

mac os applications

PyTorch implementation of batched bi-RNN encoder and attention-decoder.

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

RWKV (Receptance Weighted Key Value) is a RNN with Transformer-level performance

Library - Vanilla, ViT, DeiT, BERT, GPT

☕ A tool to generate requirements.txt for Python project, and more than that. (IT IS NOT A PACKAGE MANAGEMENT TOOL)

RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference,…

Native Ubuntu installations for Apple silicon hardware

SSHFS For Windows

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

A flexible framework for solving PDEs with modern spectral methods.

All the handwritten notes 📝 and source code files 🖥️ used in my YouTube Videos on Machine Learning & Simulation (https://www.youtube.com/channel/UCh0P7KwJhuQ4vrzc3IRuw4Q)

Python script solving the Burgers' equation (équation de Burgers) 1D by using FFT pseudo-spectral method.