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aave_brownie_py

battery-optimisation-with-drl

Grid-scale li-ion battery optimisation for wholesale market arbitrage, using pytorch implementation of dqn, double dueling dqn and a noisy network dqn.

causaltransformer

Code for the paper "Causal Transformer for Estimating Counterfactual Outcomes"

coursera-gan-specialization

Programming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai

d2l-en

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 400 universities from 60 countries including Stanford, MIT, Harvard, and Cambridge.

day-ahead-probablistic-forecasting-with-quantile-regression

Using an integrated pinball-loss objective function in various recurrent based deep learning architectures made with keras to simultaneously produce probabilistic forecasts for UK wind, solar, demand and price forecasts.

deep-generative-moeling

An Introduction to Deep Generative Modelling by Examples

deep-learning-for-molecules-materials-book

Deep learning for molecules and materials book

deep-learning-paper-implementation

🧑‍🏫 59 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

deep-reinforcement-learning-algorithms-with-pytorch

PyTorch implementations of deep reinforcement learning algorithms and environments

deep-reinforcement-learning-optimal-control

This repository contains PyTorch implementations of deep reinforcement learning algorithms and environments for Robotics and Controls. The goal of this project is to include engineering applications for industrial optimization. I reproduce the results of several model-free and modelbased RL algorithms in continuous and discrete action domains.

deep-reinforcement-learning-windfarm

This repository contains the source code and data for the application of Deep Reinforcement Learning for Active Wake Control using Wind Farm Data.

deepar-pytorch

Pytorch implementation od DeepAR model for time series forecasting

demand_forecast

diffusion_models

A series of tutorial notebooks on denoising diffusion probabilistic models in PyTorch

dyn-gfn

DynGFN: Bayesian Dynamic Causal Discovery using Generative Flow Networks

ethereumbook

Mastering Ethereum, by Andreas M. Antonopoulos, Gavin Wood

foundry-defi-stablecoin-f23

Stable Coin in Foundry

foundry-full-course-f23

foundry-fund-me-f23

gan-optimization-landscape

code to reproduce the empirical results in the research paper

generative-design-for-drug-discovery

Gen-3D is a Generative Data Benchmark design for Drug Discovery. This is code use a subset of data from DBAASP suited for active learning for generating peptides and scVelo - RNA velocity generalized through dynamical modeling.

gflownet

GFlowNet library specialized for graph & molecular data

gfn-benchmarks

This repo is a reconstitution of the most popular GFN algorithms and will serve as a banchmark.

gnn-with-tensorflow

TensorFlow GNN is a library to build Graph Neural Networks on the TensorFlow platform.

gpt-neox-for-time-series-forecasting

This repository records all advanced techniques for training large-scale language models on GPUs for Time Series Forecasting.

ivado-ap1fr

Introduction to Deep Learning workshop

jax-for-fast-computation

JAX implementation for dynamic Programming and Reinforcement Learning

jeff-deep_learning

Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks

lambo

Code to reproduce experiments in "Accelerating Bayesian Optimization for Protein Design with Denoising Autoencoders" (Stanton et al 2022)