Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.

🔍 LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your d…

Readings in the History of Programming

A curated and opinionated list of resources for Chief Technology Officers, with the emphasis on startups

A resource list for causality in statistics, data science and physics

causal inference in python, have been reading judea pearl's book of why

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphic…

Official repository for the paper "A Modern Self-Referential Weight Matrix That Learns to Modify Itself" (ICML 2022 & NeurIPS 2021 Deep RL Workshop) and "Accelerating Neural Self-Improvement via Bo…

Official PyTorch implementation of the paper: "Solving ImageNet: a Unified Scheme for Training any Backbone to Top Results" (2022)

Remote heart rate detection through Eulerian magnification of face videos

Probabilistic data structures in python http:https://pyprobables.readthedocs.io/en/latest/index.html

A suite of tools for managing crowdsourcing tasks from the inception through to data packaging for research use.

Massively Parallel Deep Reinforcement Learning. 🔥

FinRL: Financial Reinforcement Learning. 🔥

📺 Discover the latest machine learning / AI courses on YouTube.

A simple but complete full-attention transformer with a set of promising experimental features from various papers

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…

High-performance metaheuristics for optimization coded purely in Julia.

Official PyTorch implementation of GroupViT: Semantic Segmentation Emerges from Text Supervision, CVPR 2022.

Code for "MetaMorph: Learning Universal Controllers with Transformers", Gupta et al, ICLR 2022

Break the linear presentation of Jupyter Notebooks with sticky cells!

Testing the effectiveness of practical implementations of adversarial examples against facial recognition.

Code for Parameter Prediction for Unseen Deep Architectures (NeurIPS 2021)

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

95.47% on CIFAR10 with PyTorch

Linear Operators for Julia

The official PyTorch implementation - Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective (CVPR'22).

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