Distributional simplicity bias and effective convexity in Energy Based Models
Fuente:
arXiv
Guardado en:
| Autores principales: | Decelle, Aurélien, Gómez, Alfonso de Jesús Navas, Seoane, Beatriz |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Inferring Higher-Order Couplings with Neural Networks
por: Decelle, Aurélien, et al.
Publicado: (2025)
por: Decelle, Aurélien, et al.
Publicado: (2025)
Inferring effective couplings with Restricted Boltzmann Machines
por: Decelle, Aurélien, et al.
Publicado: (2023)
por: Decelle, Aurélien, et al.
Publicado: (2023)
Explaining the effects of non-convergent sampling in the training of Energy-Based Models
por: Agoritsas, Elisabeth, et al.
Publicado: (2023)
por: Agoritsas, Elisabeth, et al.
Publicado: (2023)
Cascade of phase transitions in the training of Energy-based models
por: Bachtis, Dimitrios, et al.
Publicado: (2024)
por: Bachtis, Dimitrios, et al.
Publicado: (2024)
The Copycat Perceptron: Smashing Barriers Through Collective Learning
por: Catania, Giovanni, et al.
Publicado: (2023)
por: Catania, Giovanni, et al.
Publicado: (2023)
A theoretical framework for overfitting in energy-based modeling
por: Catania, Giovanni, et al.
Publicado: (2025)
por: Catania, Giovanni, et al.
Publicado: (2025)
On the role of non-linear latent features in bipartite generative neural networks
por: Bonnaire, Tony, et al.
Publicado: (2025)
por: Bonnaire, Tony, et al.
Publicado: (2025)
Fast and Functional Structured Data Generators Rooted in Out-of-Equilibrium Physics
por: Carbone, Alessandra, et al.
Publicado: (2023)
por: Carbone, Alessandra, et al.
Publicado: (2023)
Thermodynamics of bidirectional associative memories
por: Barra, Adriano, et al.
Publicado: (2022)
por: Barra, Adriano, et al.
Publicado: (2022)
Fast training and sampling of Restricted Boltzmann Machines
por: Béreux, Nicolas, et al.
Publicado: (2024)
por: Béreux, Nicolas, et al.
Publicado: (2024)
PRIVET: Privacy Metric Based on Extreme Value Theory
por: Szatkownik, Antoine, et al.
Publicado: (2025)
por: Szatkownik, Antoine, et al.
Publicado: (2025)
Uncovering statistical structure in large-scale neural activity with Restricted Boltzmann Machines
por: Béreux, Nicolas, et al.
Publicado: (2026)
por: Béreux, Nicolas, et al.
Publicado: (2026)
The Symmetric Perceptron: a Teacher-Student Scenario
por: Catania, Giovanni, et al.
Publicado: (2026)
por: Catania, Giovanni, et al.
Publicado: (2026)
Predicting large scale cosmological structure evolution with generative adversarial network-based autoencoders
por: Ullmo, Marion, et al.
Publicado: (2024)
por: Ullmo, Marion, et al.
Publicado: (2024)
Cubic regularized subspace Newton for non-convex optimization
por: Zhao, Jim, et al.
Publicado: (2024)
por: Zhao, Jim, et al.
Publicado: (2024)
Trapped by simplicity: When Transformers fail to learn from noisy features
por: Peters, Evan, et al.
Publicado: (2026)
por: Peters, Evan, et al.
Publicado: (2026)
Differentially Private Non-convex Distributionally Robust Optimization
por: Xu, Difei, et al.
Publicado: (2026)
por: Xu, Difei, et al.
Publicado: (2026)
Large-Scale Non-convex Stochastic Constrained Distributionally Robust Optimization
por: Zhang, Qi, et al.
Publicado: (2024)
por: Zhang, Qi, et al.
Publicado: (2024)
Detecting critical treatment effect bias in small subgroups
por: De Bartolomeis, Piersilvio, et al.
Publicado: (2024)
por: De Bartolomeis, Piersilvio, et al.
Publicado: (2024)
Distributional Energy-Based Models for Uncertainty-Aware Structured LLM Reasoning
por: Manchingal, Shireen Kudukkil, et al.
Publicado: (2026)
por: Manchingal, Shireen Kudukkil, et al.
Publicado: (2026)
Unbiased and Sign Compression in Distributed Learning: Comparing Noise Resilience via SDEs
por: Compagnoni, Enea Monzio, et al.
Publicado: (2025)
por: Compagnoni, Enea Monzio, et al.
Publicado: (2025)
Simulation-Based Inference for Adaptive Experiments
por: Cho, Brian M, et al.
Publicado: (2025)
por: Cho, Brian M, et al.
Publicado: (2025)
Distributional bias compromises leave-one-out cross-validation
por: Austin, George I., et al.
Publicado: (2024)
por: Austin, George I., et al.
Publicado: (2024)
Probabilistic bias adjustment of seasonal predictions of Arctic Sea Ice Concentration
por: Gooya, Parsa, et al.
Publicado: (2025)
por: Gooya, Parsa, et al.
Publicado: (2025)
Efficient Matroid Bandit Linear Optimization Leveraging Unimodality
por: Delage, Aurélien, et al.
Publicado: (2025)
por: Delage, Aurélien, et al.
Publicado: (2025)
EVaR-Optimal Arm Identification in Bandits
por: Ahmadipour, Mehrasa, et al.
Publicado: (2025)
por: Ahmadipour, Mehrasa, et al.
Publicado: (2025)
Flows on convex polytopes
por: Diederen, Tomek, et al.
Publicado: (2025)
por: Diederen, Tomek, et al.
Publicado: (2025)
Energy-Based Models for Continual Learning
por: Li, Shuang, et al.
Publicado: (2020)
por: Li, Shuang, et al.
Publicado: (2020)
On the effects of biased quantum random numbers on the initialization of artificial neural networks
por: Heese, Raoul, et al.
Publicado: (2021)
por: Heese, Raoul, et al.
Publicado: (2021)
Byzantine Failures Harm the Generalization of Robust Distributed Learning Algorithms More Than Data Poisoning
por: Boudou, Thomas, et al.
Publicado: (2025)
por: Boudou, Thomas, et al.
Publicado: (2025)
Cognitively Inspired Energy-Based World Models
por: Gladstone, Alexi, et al.
Publicado: (2024)
por: Gladstone, Alexi, et al.
Publicado: (2024)
Model Agnostic Differentially Private Causal Inference
por: Lebeda, Christian Janos, et al.
Publicado: (2025)
por: Lebeda, Christian Janos, et al.
Publicado: (2025)
On the expressiveness and spectral bias of KANs
por: Wang, Yixuan, et al.
Publicado: (2024)
por: Wang, Yixuan, et al.
Publicado: (2024)
An energy-efficient learning solution for the Agile Earth Observation Satellite Scheduling Problem
por: Mercado-Martínez, Antonio M., et al.
Publicado: (2025)
por: Mercado-Martínez, Antonio M., et al.
Publicado: (2025)
Tighter Privacy Auditing of DP-SGD in the Hidden State Threat Model
por: Cebere, Tudor, et al.
Publicado: (2024)
por: Cebere, Tudor, et al.
Publicado: (2024)
Goal-Oriented Lower-Tail Calibration of Gaussian Processes for Bayesian Optimization
por: Pion, Aurélien, et al.
Publicado: (2026)
por: Pion, Aurélien, et al.
Publicado: (2026)
Design-marginal calibration of Gaussian process predictive distributions: Bayesian and conformal approaches
por: Pion, Aurélien, et al.
Publicado: (2025)
por: Pion, Aurélien, et al.
Publicado: (2025)
Generating Physically Consistent Molecules with Energy-Based Models
por: Griesbacher, Christoph, et al.
Publicado: (2026)
por: Griesbacher, Christoph, et al.
Publicado: (2026)
Particle Dynamics for Latent-Variable Energy-Based Models
por: Tang, Shiqin, et al.
Publicado: (2025)
por: Tang, Shiqin, et al.
Publicado: (2025)
Energy-Based Models for Predicting Mutational Effects on Proteins
por: Soga, Patrick, et al.
Publicado: (2025)
por: Soga, Patrick, et al.
Publicado: (2025)
Ejemplares similares
-
Inferring Higher-Order Couplings with Neural Networks
por: Decelle, Aurélien, et al.
Publicado: (2025) -
Inferring effective couplings with Restricted Boltzmann Machines
por: Decelle, Aurélien, et al.
Publicado: (2023) -
Explaining the effects of non-convergent sampling in the training of Energy-Based Models
por: Agoritsas, Elisabeth, et al.
Publicado: (2023) -
Cascade of phase transitions in the training of Energy-based models
por: Bachtis, Dimitrios, et al.
Publicado: (2024) -
The Copycat Perceptron: Smashing Barriers Through Collective Learning
por: Catania, Giovanni, et al.
Publicado: (2023)