Author

L. Rokach

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Open access Oct 2026

Multi-Objective-Conditioned-Return-Blocks Decision Transformer: A Novel Approach for Multi-Objective De Novo Drug Design.

MOTIVATION Designing novel molecules that simultaneously satisfy several, often conflicting, properties is a long-standing challenge in drug design. While recent deep learning advances optimize single targets effectively, navigating the trade-offs required for multiple objectives remains a difficult problem. RESULTS...

Eyal Mazuz, Or Gindes, L. Rokach et al. · Bioinformatics · 0 citations

#machine learning Preprint Sep 2026

TemporalGraphLLM: Temporal Graph Neural Networks with Large Language Models for Dynamic Text-Attributed Graphs

Dynamic text-attributed graphs (DTAGs), where nodes, edges, and textual attributes evolve over time, are crucial in applications such as social networks, citation graphs, and knowledge graphs. However, existing approaches struggle to jointly model the temporal evolution of graph structures and the semantic richness of...

Moran Beladev, Orly Eitan, Gilad Katz et al. · 0 citations

Open access Jul 2026

MEMTIER: Tiered Retrieval, Session-Level Injection, and Typed Consolidation for Long-Running LLM Agents

MEMTIER, a tiered memory architecture and consolidation framework for an open-source agent runtime and three questions: what to store, what to inject, and what to keep are studied and cast agent memory as a pattern recognition problem: recognizing which session patterns carry evidence and which knowledge types to retai...

Bronislav Sidik, L. Rokach · Algorithms · 0 citations

Open access Jul 2026

Risk-Guided Screening for Atrial Fibrillation Using Electronic Health Records

The EHR-based machine learning model, FIND-AF 2.0, identifies a high-risk subpopulation for AF diagnosis among patients at elevated risk of stroke and could enable scalable, EHR-driven, risk-guided AF screening.

R. Nadarajah, Jianhua Wu, A. Wahab et al. · Circulation · 0 citations