Python code for "Probabilistic Machine learning" book by Kevin Murphy

Repository of notes, code and notebooks in Python for the book Pattern Recognition and Machine Learning by Christopher Bishop

Practical course about Large Language Models.

Biological foundation modeling from molecular to genome scale

KernelBench: Can LLMs Write GPU Kernels? - Benchmark + Toolkit with Torch -> CUDA (+ more DSLs)

Building a Bayesian deep learning classifier

Kolmogorov-Arnold Networks (KAN) using Chebyshev polynomials instead of B-splines.

A repository consisting of paper/architecture replications of classic/SOTA AI/ML papers in pytorch

Train VAE like a boss

A general framework for inference-time scaling and steering of diffusion models with arbitrary rewards.

A repo for all spark examples using Rapids Accelerator including ETL, ML/DL, etc.

One protein is all you need

Repository of notes, code and notebooks in Python for the book "Reinforcement Learning: An Introduction" by Richard S. Sutton and Andrew G. Barto

Code for "Calibrating Generative Models" by Henry Smith, Nathaniel Diamant, and Brian Trippe

Cross-modality matching and prediction with labeled Gromov-Wasserstein Optimal Transport.

Diffusion model for generating cat images

GPT-2 Model Compression Experiment