Code for the paper "Analyzing inverse problems with invertible neural networks." (2018)

A Python library for amortized Bayesian workflows using generative neural networks.

Contains legacy code and model examples for the paper "BayesFlow: Learning complex stochastic models with invertible neural networks"

🌍 A curated list of MIT faculty that tackle climate change with machine learning for applying students, undergraduates, or others

Simplifying reinforcement learning for complex game environments

🔥Highlighting the top ML papers every week.

Transformer implementation from scratch (in PyTorch)

Tufte-inspired MIT template thesis

Keras Temporal Convolutional Network. Supports Python and R.

A basic framework for your PyTorch projects

MIT EECS Thesis Proposal Template

Sequence modeling benchmarks and temporal convolutional networks

PyTorch implementations of several SOTA backbone deep neural networks (such as ResNet, ResNeXt, RegNet) on one-dimensional (1D) signal/time-series data.

Learning in infinite dimension with neural operators.

Examples of how to create colorful, annotated equations in Latex using Tikz.

📚 Freely available programming books