Overview:Machine Learning libraries like PyTorch, TensorFlow, and JAX help developers build, train, and deploy AI models efficiently.PyTorch is widely used in A ...

Can symbolic regression be the key to transforming opaque deep learning models into interpretable, closed-form mathematical equations? or Say you have trained your deep learning model. It works. But ...

A unified PyTorch library providing easy access to state-of-the-art Linear RNN architectures for sequence modeling. The technical report of this system was accepted to EACL Student Research Workshop ...

Google's TorchTPU aims to enhance TPU compatibility with PyTorch Google seeks to help AI developers reduce reliance on Nvidia's CUDA ecosystem TorchTPU initiative is part of Google's plan to attract ...

Student cognitive modeling is a fundamental task in the intelligence education field. It serves as the basis for various downstream applications, such as personalized educational content ...

This paper focuses on developing a machine learning model for predicting initial beam parameters for the Long Baseline Neutrino Facility (LBNF) beamline using downstream muon monitor data. Parameters ...

Some pytorch features (as torch.distributed.tensor.experimental.register_sharding, see https://docs.pytorch.org/docs/stable/distributed.tensor.html) appear to require ...

Artificial intelligence (AI) models, frequently built using deep neural networks (DNNs), have become integral to many aspects of modern life. However, the vast amount of data they process is not ...

ABSTRACT: As the integration of Large Language Models (LLMs) into scientific R&D accelerates, the associated privacy risks become increasingly critical. Scientific NoSQL repositories, which often ...

Abstract: Vision Transformer (ViT) models which were recently introduced by the transformer architecture have shown to be very competitive and often become a popular alternative to Convolutional ...