Python Library for Transaction Cost Analysis and Market Simulation - Scaling Law in Quantitative Trading

A toolkit for scaling law research ⚖

Official code for the paper, "Scaling Offline Model-Based RL via Jointly-Optimized World-Action Model Pretraining"

[ICML 2023] "Data Efficient Neural Scaling Law via Model Reusing" by Peihao Wang, Rameswar Panda, Zhangyang Wang

[NeurIPS 2023] Multi-fidelity hyperparameter optimization with deep power laws that achieves state-of-the-art results across diverse benchmarks.

code for Scaling Laws for Language Transfer Learning

A method for calculating scaling laws for LLMs from publicly available models

🌹[ICML 2024] Selecting Large Language Model to Fine-tune via Rectified Scaling Law

[NeurIPS 2023] Multi-fidelity hyperparameter optimization with deep power laws that achieves state-of-the-art results across diverse benchmarks.