However, the M4 generation has an improved Nerual Engine that will make on-device models run better. Some rumors suggest that Apple could introduce thinner MacBooks within the next iteration ...
Computing in memory optimizes data handling by performing operations directly in memory, ideal for high-speed data processing needs. This compilation highlights its technologies and applications, ...
Library for Jacobian descent with PyTorch. It enables optimization of neural networks with multiple losses (e.g. multi-task learning).
Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R ...
This repository contains a reading list of papers on Time Series Forecasting/Prediction (TSF) and Spatio-Temporal Forecasting/Prediction (STF). These papers are ...
Python library for solving reinforcement learning (RL) problems using generative models (e.g. Diffusion Models).