Image de couverture de livre

Understanding Biology in the Age of Artificial Intelligence

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Lawrence, Elsa, El-Shazly, Adham, Seal, Srijit, Joshi, Chaitanya K, Liò, Pietro, Singh, Shantanu, Bender, Andreas, Sormanni, Pietro, Greenig, Matthew
Format:	Preprint
Publié:	2024
Sujets:	Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Score-Based Generative Models for Designing Binding Peptide Backbones
par: Boom, John D, et autres
Publié: (2023)

Towards Mechanistic Interpretability of Graph Transformers via Attention Graphs
par: El, Batu, et autres
Publié: (2025)

IgCraft: A versatile sequence generation framework for antibody discovery and engineering
par: Greenig, Matthew, et autres
Publié: (2025)

Metalearning-Informed Competence in Children: Implications for Responsible Brain-Inspired Artificial Intelligence
par: Singh, Chaitanya
Publié: (2023)

CALF: Communication-Aware Learning Framework for Distributed Reinforcement Learning
par: Purves, Carlos, et autres
Publié: (2026)

How Smoothing is N-simplicial Attention?
par: Dussolle, Alexandre, et autres
Publié: (2025)

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers
par: Sun, Bohang, et autres
Publié: (2025)

GenRec: Generative Sequential Recommendation with Large Language Models
par: Cao, Panfeng, et autres
Publié: (2024)

DCAE-SR: Design of a Denoising Convolutional Autoencoder for reconstructing Electrocardiograms signals at Super Resolution
par: Lomoio, Ugo, et autres
Publié: (2024)

Sphere Neural-Networks for Rational Reasoning
par: Dong, Tiansi, et autres
Publié: (2024)

UESA-Net: U-Shaped Embedded Multidirectional Shrinkage Attention Network for Ultrasound Nodule Segmentation
par: Shi, Tangqi, et autres
Publié: (2025)

Actionable Interpretability via Causal Hypergraphs: Unravelling Batch Size Effects in Deep Learning
par: Sun, Zhongtian, et autres
Publié: (2025)

Superposition in Graph Neural Networks
par: Pertl, Lukas, et autres
Publié: (2025)

Algebraic Priors for Approximately Equivariant Networks
par: Ali, Riccardo, et autres
Publié: (2025)

Hierarchical Planning for Complex Tasks with Knowledge Graph-RAG and Symbolic Verification
par: Cornelio, Cristina, et autres
Publié: (2025)

Symmetry and Generalisation in Neural Approximations of Renormalisation Transformations
par: Ashworth, Cassidy, et autres
Publié: (2025)

FLUID-LLM: Learning Computational Fluid Dynamics with Spatiotemporal-aware Large Language Models
par: Zhu, Max, et autres
Publié: (2024)

Polynomial Neural Sheaf Diffusion: A Spectral Filtering Approach on Cellular Sheaves
par: Borgi, Alessio, et autres
Publié: (2025)

Transformers are Graph Neural Networks
par: Joshi, Chaitanya K.
Publié: (2025)

KAPLAN: Kolmogorov-Arnold Prognostic Learnable Activation Networks for Survival Analysis
par: Logothetis, Stelios Boulitsakis, et autres
Publié: (2026)

On the Expressive Power of Geometric Graph Neural Networks
par: Joshi, Chaitanya K., et autres
Publié: (2023)

An AI Monkey Gets Grapes for Sure -- Sphere Neural Networks for Reliable Decision-Making
par: Dong, Tiansi, et autres
Publié: (2026)

A Decade in a Systematic Review: The Evolution and Impact of Cell Painting
par: Seal, Srijit, et autres
Publié: (2024)

KG4Diagnosis: A Hierarchical Multi-Agent LLM Framework with Knowledge Graph Enhancement for Medical Diagnosis
par: Zuo, Kaiwen, et autres
Publié: (2024)

MoRE-GNN: Multi-omics Data Integration with a Heterogeneous Graph Autoencoder
par: Wang, Zhiyu, et autres
Publié: (2025)

Multi-Scale Protein Structure Modelling with Geometric Graph U-Nets
par: Liu, Chang, et autres
Publié: (2025)

Will More Expressive Graph Neural Networks do Better on Generative Tasks?
par: Zou, Xiandong, et autres
Publié: (2023)

Sparsity is All You Need: Rethinking Biological Pathway-Informed Approaches in Deep Learning
par: Caranzano, Isabella, et autres
Publié: (2025)

Enhancing Surgical Documentation through Multimodal Visual-Temporal Transformers and Generative AI
par: Georgenthum, Hugo, et autres
Publié: (2025)

A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems
par: Duval, Alexandre, et autres
Publié: (2023)

An end-to-end attention-based approach for learning on graphs
par: Buterez, David, et autres
Publié: (2024)

Entropy-Lens: Uncovering Decision Strategies in LLMs
par: Ali, Riccardo, et autres
Publié: (2025)

Sheaves Reloaded: A Directional Awakening
par: Fiorini, Stefano, et autres
Publié: (2025)

Flows, straight but not so fast: Exploring the design space of Rectified Flows in Protein Design
par: Chen, Junhua, et autres
Publié: (2025)

ElegansNet: a brief scientific report and initial experiments
par: Bardozzo, Francesco, et autres
Publié: (2023)

An Empirical Investigation of Neural ODEs and Symbolic Regression for Dynamical Systems
par: Ioannou, Panayiotis, et autres
Publié: (2026)

xAI-Drop: Don't Use What You Cannot Explain
par: De Luca, Vincenzo Marco, et autres
Publié: (2024)

TabMDA: Tabular Manifold Data Augmentation for Any Classifier using Transformers with In-context Subsetting
par: Margeloiu, Andrei, et autres
Publié: (2024)

Artificial Intelligence: Beyound Ocularcentrism, the New Age of Humans Beyond the Spectacle
par: Moussaoui, Mustapha El
Publié: (2026)

The Explanation Necessity for Healthcare AI
par: Mamalakis, Michail, et autres
Publié: (2024)