Deep Learning
ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning
Many of those tasks have been addressed on datasets created with single climate models.
Nearly Optimal VC-Dimension and Pseudo-Dimension Bounds for Deep Neural Network Derivatives
Obtaining such bounds for DNN derivatives is much more difficult due to their complex compositional structures.
Cognitive Steering in Deep Neural Networks via Long-Range Modulatory Feedback Connections
Here we introduce cognitively and biologically-inspired long-range modulatory pathways to enable'cognitive steering' in vision
LeanDojo: Theorem Proving with Retrieval-Augmented Language Models
It is inexpensive and needs only one GPU week of training.
the performance of various LLMs on code synthesis. However, these test-cases can be limited in both quantity and quality for fully assessing the functional
Program synthesis has been long studied with recent approaches focused on directly using the power of Large Language Models (LLMs) to generate code.
Fed-CO2: Cooperation of Online and Offline Models for Severe Data Heterogeneity in Federated Learning
Federated Learning (PFL) has emerged, where personalized models are trained for individual clients.