Latest Articles for Machine Learning

Analyzing the efficiency and potential of quantum-inspired algorithms in classical computing.

We introduce a quick method for CIFAR-10 training, enhancing accuracy and speed.

Introducing ME-ViT, a memory-efficient FPGA accelerator for Vision Transformers.

New methods enhance predictions of complex systems using data-driven reduced-order models.

New methods improve accuracy in answering complex questions with updated information.

Quantum computing boosts machine learning efficiency and capabilities through innovative collaboration.

A framework to improve the safety and reliability of large language models.

A new method improves clarity in analyzing gene interactions using machine learning.

New model improves circuit design prediction through directed hypergraphs.

Research investigates gender bias by evaluating statistical and causal fairness in NLP models.

Exploring self-consistency training's role in enhancing Hamiltonian prediction for molecular properties.

New method enhances uncertainty quantification in DeepONets using Ensemble Kalman Inversion.

SVGCraft generates vector graphics from text descriptions with high quality and speed.

This work presents a systematic framework for analyzing machine learning algorithms.

A new method improves image-text alignment by reducing single tag bias.

A novel approach to efficiently solve Ising models using neural networks.

A new method enhances depth maps by focusing on edge clarity.

This study focuses on improving adaptability in deep reinforcement learning algorithms.

New model improves robotic fruit harvesting accuracy using 3D point cloud data.

A new method enhances quality control for solar images at the National Solar Observatory.

A study on how Large Language Models can improve vulnerability detection in software.

A new method enhances deep learning models for imbalanced datasets.

A new method boosts language model responsiveness to unfamiliar queries.

An exploration of how language models predict future tokens compared to human thinking.

Exploring how quantum computing enhances diffusion models for better image generation.

A novel approach enhances language model reliability through self-healing mechanisms.

A method combining Koopman operator and kernel approaches for improved nonlinear system control.

A new method addresses key issues in continual learning: plasticity and forgetting.

FedD2S enhances Federated Learning by personalizing models while preserving data privacy.

This paper examines how data affects the evaluation of NLP models.

This article discusses deep learning techniques for pricing complex path-dependent options.

Examining performance challenges faced by rotation invariant algorithms in noisy and sparse data scenarios.

A new method to enhance trajectory prediction across varying observation lengths.

This article discusses how data-driven methods improve control systems through simplified models.

A new approach combines machine learning with fluid dynamics for enhanced simulations.

Explores the privacy risks and defenses related to synthetic data created by GANs.

A look into dense and generative retrieval techniques and their impact.

A new framework enhances how we assess coherence in texts.

Strategies for improving variational autoencoders in handling incomplete datasets.

A method to enhance 3D object detection using LiDAR data.