Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025)

Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
IEEE

Dual-Stream Contrastive Learning for Medical Visual Representations Using Synthetic Images Generated by Latent Diffusion Model

Abstract: Deep learning-based medical image processing methods can enhance diagnostic accuracy while significantly accelerating clinical decision workflows. However, in order to learn better visual ...
IEEE

Contrastive Learning Algorithm for Low-Resource Cryptographic Attack Event Detection

Abstract: The widespread use of the internet has led to frequent cryptographic attack event incidents, which pose various risks, including the leakage of personal information, privacy data, identity ...
Yicai Global

Chinese Scientists Develop AI-Driven Ultra-Fast Drug Screening Platform

(Yicai) Jan. 13 -- A team of scientists at Tsinghua University in China have developed an artificial intelligence-driven ...
News-Medical.Net

AI trained on sleep data predicts future disease and mortality years in advance

The SleepFM model reveals how sleep analysis can predict disease risk, offering insights into sleep's role as a vital health ...
Frontiers

DMAGCL: A dual-masked adaptive graph contrastive learning framework for predicting circRNA-drug sensitivity

Circular RNAs (circRNAs) are a unique class of non-coding RNAs with stable covalently closed structures that play key regulatory roles in gene expression and drug response. However, experimental ...
GitHub

GRACE: Generative Representation Learning via Contrastive Policy Optimization

@misc{sun2025gracegenerativerepresentationlearning, title={GRACE: Generative Representation Learning via Contrastive Policy Optimization}, author={Jiashuo Sun and ...
C&EN

Noise-Consistent Hypergraph Autoencoder Based on Contrastive Learning for Cancer ceRNA Association Prediction in Complex Biological Regulatory Networks

Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, Changchun 130012, China ...
C&EN

AVP-HNCL: Innovative Contrastive Learning with a Queue-Based Negative Sampling Strategy for Dual-Phase Antiviral Peptide Prediction

School of Computer Science and Technology, Hainan University, Haikou 570228, China Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu ...
EurekAlert!

Heterogeneous spatio-temporal graph contrastive learning for point-of-interest recommendation

As one of the most crucial topics in the recommendation system field, Point-of-Interest (POI) recommendation aims to recommending potential interesting POIs to users. Recently, graph neural networks ...