A lecture note for understanding deep learning

MIT IAP short course: Matrix Calculus for Machine Learning and Beyond

Code for NAACL 2025 Conference Paper: Take the essence and discard the dross- A Rethinking on Data Selection for Fine-Tuning Large Language Models

🫐 SimpleDarkBlue - A simple and clear LaTeX Beamer theme

[ICLR 2025 Workshop] "Landscape of Thoughts: Visualizing the Reasoning Process of Large Language Models"

Minimal and annotated implementations of key ideas from modern deep learning research.

Train your AI self, amplify you, bridge the world

Efficient Triton Kernels for LLM Training

Understanding R1-Zero-Like Training: A Critical Perspective

Fully open reproduction of DeepSeek-R1

s1: Simple test-time scaling

PyHessian is a Pytorch library for second-order based analysis and training of Neural Networks

NanoGPT (124M) in 3 minutes

EPFL Course - Optimization for Machine Learning - CS-439

This is a list of peer-reviewed representative papers on deep learning dynamics (optimization dynamics of neural networks). The success of deep learning attributes to both network architecture and …

AI Logging for Interpretability and Explainability🔬

Influence Functions with (Eigenvalue-corrected) Kronecker-Factored Approximate Curvature

Influence Analysis and Estimation - Survey, Papers, and Taxonomy

[ICML 2024] LESS: Selecting Influential Data for Targeted Instruction Tuning

2024 up-to-date list of DATASETS, CODEBASES and PAPERS on Multi-Task Learning (MTL), from Machine Learning perspective.

Latency and Memory Analysis of Transformer Models for Training and Inference

Paper List for Multi-Task Learning (focus on architectures and optimization for MTL)

Skill-It! A Data-Driven Skills Framework for Understanding and Training Language Models

List of Computer Science courses with video lectures.

This is a curated list for Information Bottleneck Principle, in memory of Professor Naftali Tishby.