Copertina

Disentangling Representations through Multi-task Learning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Vafidis, Pantelis, Bhargava, Aman, Rangel, Antonio
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Artificial Intelligence Neurons and Cognition
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Stimulus-to-Stimulus Learning in RNNs with Cortical Inductive Biases
di: Vafidis, Pantelis, et al.
Pubblicazione: (2024)

Learning Cross-Atlas Consistent Brain Disorder Representations via Disentangled Multi-Atlas Functional Connectivity Learning
di: Chen, Minheng, et al.
Pubblicazione: (2026)

Disentangled Representations for Causal Cognition
di: Torresan, Filippo, et al.
Pubblicazione: (2024)

Learning Human-Aligned Representations with Contrastive Learning and Generative Similarity
di: Marjieh, Raja, et al.
Pubblicazione: (2024)

Bridging Foundation Models and Efficient Architectures: A Modular Brain Imaging Framework with Local Masking and Pretrained Representation Learning
di: Wang, Yanwen, et al.
Pubblicazione: (2025)

Cross-Modal Representational Knowledge Distillation for Enhanced Spike-Informed LFP Modeling
di: Erturk, Eray, et al.
Pubblicazione: (2025)

BaRISTA: Brain Scale Informed Spatiotemporal Representation of Human Intracranial Neural Activity
di: Oganesian, Lucine L., et al.
Pubblicazione: (2025)

Understanding Transformers through the Lens of Pavlovian Conditioning
di: Qiao, Mu
Pubblicazione: (2025)

Characterizing higher-order representations through generative diffusion models explains human decoded neurofeedback performance
di: Asrari, Hojjat Azimi, et al.
Pubblicazione: (2025)

Learning to Abstract Visuomotor Mappings using Meta-Reinforcement Learning
di: Velazquez-Vargas, Carlos A., et al.
Pubblicazione: (2024)

Experimental Design for Multi-Channel Imaging via Task-Driven Feature Selection
di: Blumberg, Stefano B., et al.
Pubblicazione: (2022)

Multi-dataset Joint Pre-training of Emotional EEG Enables Generalizable Affective Computing
di: Zhang, Qingzhu, et al.
Pubblicazione: (2025)

Deep Learning without Weight Symmetry
di: Ji-An, Li, et al.
Pubblicazione: (2024)

Learning Dynamics of RNNs in Closed-Loop Environments
di: Ger, Yoav, et al.
Pubblicazione: (2025)

Contrastive Self-Supervised Learning As Neural Manifold Packing
di: Zhang, Guanming, et al.
Pubblicazione: (2025)

Learning reveals invisible structure in low-rank RNNs
di: Ger, Yoav, et al.
Pubblicazione: (2026)

NeuroGraph: Benchmarks for Graph Machine Learning in Brain Connectomics
di: Said, Anwar, et al.
Pubblicazione: (2023)

Critical Learning Periods Emerge Even in Deep Linear Networks
di: Kleinman, Michael, et al.
Pubblicazione: (2023)

Cortex-Inspired Continual Learning: Unsupervised Instantiation and Recovery of Functional Task Networks
di: McKee, Kevin, et al.
Pubblicazione: (2026)

Graph Autoencoders for Embedding Learning in Brain Networks and Major Depressive Disorder Identification
di: Noman, Fuad, et al.
Pubblicazione: (2021)

DSAM: A Deep Learning Framework for Analyzing Temporal and Spatial Dynamics in Brain Networks
di: Thapaliya, Bishal, et al.
Pubblicazione: (2024)

Sophisticated Learning: A novel algorithm for active learning during model-based planning
di: Hodson, Rowan, et al.
Pubblicazione: (2023)

Multimodal Dreaming: A Global Workspace Approach to World Model-Based Reinforcement Learning
di: Maytié, Léopold, et al.
Pubblicazione: (2025)

Revealing Neurocognitive and Behavioral Patterns by Unsupervised Manifold Learning from Dynamic Brain Data
di: Zhou, Zixia, et al.
Pubblicazione: (2025)

Explaining Deep Learning Models for Age-related Gait Classification based on time series acceleration
di: Zheng, Xiaoping, et al.
Pubblicazione: (2023)

BrainNet-MoE: Brain-Inspired Mixture-of-Experts Learning for Neurological Disease Identification
di: Zhang, Jing, et al.
Pubblicazione: (2025)

Accuracy-Efficiency Trade-Offs in Spiking Neural Networks: A Lempel-Ziv Complexity Perspective on Learning Rules
di: Rudnicka, Zofia, et al.
Pubblicazione: (2025)

Establishing Central Sensitization Inventory Cut-off Values in patients with Chronic Low Back Pain by Unsupervised Machine Learning
di: Zheng, Xiaoping, et al.
Pubblicazione: (2023)

Compositional meta-learning through probabilistic task inference
di: Bakermans, Jacob J. W., et al.
Pubblicazione: (2025)

Semi-supervised Multimodal Representation Learning through a Global Workspace
di: Devillers, Benjamin, et al.
Pubblicazione: (2023)

Overcoming classic challenges for artificial neural networks by providing incentives and practice
di: Irie, Kazuki, et al.
Pubblicazione: (2024)

Concept Alignment
di: Rane, Sunayana, et al.
Pubblicazione: (2024)

Brain-like Variational Inference
di: Vafaii, Hadi, et al.
Pubblicazione: (2024)

The Geometry of Concepts: Sparse Autoencoder Feature Structure
di: Li, Yuxiao, et al.
Pubblicazione: (2024)

Poisson Variational Autoencoder
di: Vafaii, Hadi, et al.
Pubblicazione: (2024)

Emergent Language Symbolic Autoencoder (ELSA) with Weak Supervision to Model Hierarchical Brain Networks
di: Latheef, Ammar Ahmed Pallikonda, et al.
Pubblicazione: (2024)

Discretization of continuous input spaces in the hippocampal autoencoder
di: Amil, Adrian F., et al.
Pubblicazione: (2024)

Divide-and-Conquer Predictive Coding: a structured Bayesian inference algorithm
di: Sennesh, Eli, et al.
Pubblicazione: (2024)

Contrasformer: A Brain Network Contrastive Transformer for Neurodegenerative Condition Identification
di: Xu, Jiaxing, et al.
Pubblicazione: (2024)

Predicting Human Brain States with Transformer
di: Sun, Yifei, et al.
Pubblicazione: (2024)