Versioned research release of the BBB permeability prediction project. This release preserves the complete source code, experimental results, documentation, figures, and reproducibility materials for the project. Contents: Phase 3: 5-fold scaffold CV classical ML (RF AUROC 0.921+/-0.024) Phase 4: Chemprop GNN ensemble...
Devarshi Hatwar· Zenodo (CERN European Organi...· 0 citations
Versioned research release of the BBB permeability prediction project. This release preserves the complete source code, experimental results, documentation, figures, and reproducibility materials for the project. Contents: Phase 3: 5-fold scaffold CV classical ML (RF AUROC 0.921+/-0.024) Phase 4: Chemprop GNN ensemble...
Devarshi Hatwar· Zenodo (CERN European Organi...· 0 citations
Artificial Intelligence (AI) is increasingly being applied to digital circuit design to assist with circuit analysis, optimization, and automation. This study examines the role of AI in digital circuit design, focusing on Graph Neural Networks (GNNs), Reinforcement Learning (RL), and Generative AI. These approaches can...
Rainer Marc Bindoy· Zenodo (CERN European Organi...· 0 citations
This educational module presents a comprehensive academic introduction to Swarm and Multi-Agent Robotics within the Prep4Uni Robotics and AI curriculum. Core Theoretical and Engineering Foundations: Network Representation & Algebraic Graph Theory: Modeling multi-agent systems via time-varying graphs G = (V, E), topolog...
Prep4Uni.Online· Zenodo (CERN European Organi...· 0 citations
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This educational module presents a comprehensive academic introduction to Swarm and Multi-Agent Robotics within the Prep4Uni Robotics and AI curriculum. Core Theoretical and Engineering Foundations: Network Representation & Algebraic Graph Theory: Modeling multi-agent systems via time-varying graphs G = (V, E), topolog...
Prep4Uni.Online· Zenodo (CERN European Organi...· 0 citations
Artificial intelligence (AI) and Machine learning (ML) are transforming the pharmaceutical lifecycle—from target identification and lead optimization to clinical development, manufacturing, supply chain orchestration, and real-world pharmacovigilance. This review synthesizes recent advances (2018–2025) across core meth...
Shoheb Shakil Shaikh· Journal of Pharmaceutical an...· 0 citations
The ability of an optical network to resist and recover from failures and disruptions reflects its overall effectiveness. Many practitioners and researchers are striving to realize maximum survivability of optical network systems. This paper developed a hybrid Deep Learning (DL) approach for dynamic restoration in Wave...
Tzu-Chia Chen· Biomedical Signal Processing...· 0 citations
Artificial Intelligence (AI) is increasingly being applied to digital circuit design to assist with circuit analysis, optimization, and automation. This study examines the role of AI in digital circuit design, focusing on Graph Neural Networks (GNNs), Reinforcement Learning (RL), and Generative AI. These approaches can...
Rainer Marc Bindoy· Zenodo (CERN European Organi...· 0 citations
Abstract Large language models write code fluently, yet the programs they produce carry defect rates that ordinary functional evaluation seldom exposes, and detection systems that could catch these faults act too late to shape the generation that created them. This paper argues that generation and detection should be o...
Graph neural networks dominate recent work on microservice root-cause analysis, yet recent results question whether the graph contributes. Those results compare whole pipelines, so when a flat model wins one cannot tell whether structure is useless or redundant. We run the comparison they imply on RCAEval: three learne...
Imad Buljić· Zenodo (CERN European Organi...· 0 citations
We present τ-TCPN (Temporal-Cut-Point Causal Fusion Network), a deterministic, training-free framework for autonomous causal reasoning. Unlike probabilistic neural networks that rely on gradient descent and approximate inference, τ-TCPN models neurons as discrete temporal cut points with hard causal compatibility const...
You Zhang· Zenodo (CERN European Organi...· 0 citations
Assistant Professor Pat Pataranutaporn describes a new interface that lets everyday users glimpse inside an AI's neural network before their chatbot ever says a word.
Microsoft Research Blog· microsoft.comJul 13, 2026
Cryptographic code supports vital protections in modern computing systems. Learn how a new method helps verify code as developers write it while preserving speed and adaptability as it gets implemented and evolves. The post Verifying Rust cryptography in SymCrypt, from standards to code appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduJul 6, 2026
PhD student Rachel Sava, winner of the Envisioning the Future of Computing Prize, explores transformative improvements and dystopian risks of neural technology.
