Guardado en:
| Autores principales: | Ibias, Alfredo, Capala, Karol, Varma, Varun Ravi, Drozdz, Anna, Sousa, Jose |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2406.08428 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
CACTUS: a Comprehensive Abstraction and Classification Tool for Uncovering Structures
por: Gherardini, Luca, et al.
Publicado: (2023)
por: Gherardini, Luca, et al.
Publicado: (2023)
Preservation of Feature Stability in Machine Learning Under Data Uncertainty for Decision Support in Critical Domains
por: Capała, Karol, et al.
Publicado: (2024)
por: Capała, Karol, et al.
Publicado: (2024)
Optimisation Is Not What You Need
por: Ibias, Alfredo
Publicado: (2025)
por: Ibias, Alfredo
Publicado: (2025)
Knowledge Discovery using Unsupervised Cognition
por: Ibias, Alfredo, et al.
Publicado: (2024)
por: Ibias, Alfredo, et al.
Publicado: (2024)
Unsupervised Cognition
por: Ibias, Alfredo, et al.
Publicado: (2024)
por: Ibias, Alfredo, et al.
Publicado: (2024)
Beating Transformers using Synthetic Cognition
por: Ibias, Alfredo, et al.
Publicado: (2025)
por: Ibias, Alfredo, et al.
Publicado: (2025)
Distributionally Robust Causal Abstractions
por: Felekis, Yorgos, et al.
Publicado: (2025)
por: Felekis, Yorgos, et al.
Publicado: (2025)
Interval Abstractions for Robust Counterfactual Explanations
por: Jiang, Junqi, et al.
Publicado: (2024)
por: Jiang, Junqi, et al.
Publicado: (2024)
NoiseFormer -- Noise Diffused Symmetric Attention Transformer
por: Kumar, Phani, et al.
Publicado: (2026)
por: Kumar, Phani, et al.
Publicado: (2026)
Understanding the Countably Infinite: Neural Network Models of the Successor Function and its Acquisition
por: Gupta, Vima, et al.
Publicado: (2023)
por: Gupta, Vima, et al.
Publicado: (2023)
The Impact of Machine Learning Uncertainty on the Robustness of Counterfactual Explanations
por: Christodoulou, Leonidas, et al.
Publicado: (2026)
por: Christodoulou, Leonidas, et al.
Publicado: (2026)
Quantum Tunneling-Aware Machine Learning: Physics-Derived Noise Models for Robust Deployment
por: Hwang, Uiwon, et al.
Publicado: (2026)
por: Hwang, Uiwon, et al.
Publicado: (2026)
Contrastive Abstraction for Reinforcement Learning
por: Patil, Vihang, et al.
Publicado: (2024)
por: Patil, Vihang, et al.
Publicado: (2024)
Relax: Composable Abstractions for End-to-End Dynamic Machine Learning
por: Lai, Ruihang, et al.
Publicado: (2023)
por: Lai, Ruihang, et al.
Publicado: (2023)
Contextual Pre-planning on Reward Machine Abstractions for Enhanced Transfer in Deep Reinforcement Learning
por: Azran, Guy, et al.
Publicado: (2023)
por: Azran, Guy, et al.
Publicado: (2023)
Scalable Decision-Making in Stochastic Environments through Learned Temporal Abstraction
por: Luo, Baiting, et al.
Publicado: (2025)
por: Luo, Baiting, et al.
Publicado: (2025)
Constructing Optimal Noise Channels for Enhanced Robustness in Quantum Machine Learning
por: Winderl, David, et al.
Publicado: (2024)
por: Winderl, David, et al.
Publicado: (2024)
Improving Rule-based Reasoning in LLMs using Neurosymbolic Representations
por: Dhanraj, Varun, et al.
Publicado: (2025)
por: Dhanraj, Varun, et al.
Publicado: (2025)
Learning Markov State Abstractions for Deep Reinforcement Learning
por: Allen, Cameron, et al.
Publicado: (2021)
por: Allen, Cameron, et al.
Publicado: (2021)
Impact of Label Noise on Learning Complex Features
por: Vashisht, Rahul, et al.
Publicado: (2024)
por: Vashisht, Rahul, et al.
Publicado: (2024)
Abstraction for Offline Goal-Conditioned Reinforcement Learning
por: Wibault, Clarisse, et al.
Publicado: (2026)
por: Wibault, Clarisse, et al.
Publicado: (2026)
SAP: Corrective Machine Unlearning with Scaled Activation Projection for Label Noise Robustness
por: Kodge, Sangamesh, et al.
Publicado: (2024)
por: Kodge, Sangamesh, et al.
Publicado: (2024)
Predicting Solar Energy Generation with Machine Learning based on AQI and Weather Features
por: Shah, Arjun, et al.
Publicado: (2024)
por: Shah, Arjun, et al.
Publicado: (2024)
Precise Verification of Transformers through ReLU-Catalyzed Abstraction Refinement
por: Liu, Hengjie, et al.
Publicado: (2026)
por: Liu, Hengjie, et al.
Publicado: (2026)
Improving Dictionary Learning with Gated Sparse Autoencoders
por: Rajamanoharan, Senthooran, et al.
Publicado: (2024)
por: Rajamanoharan, Senthooran, et al.
Publicado: (2024)
Learning with Language-Guided State Abstractions
por: Peng, Andi, et al.
Publicado: (2024)
por: Peng, Andi, et al.
Publicado: (2024)
ARCLE: The Abstraction and Reasoning Corpus Learning Environment for Reinforcement Learning
por: Lee, Hosung, et al.
Publicado: (2024)
por: Lee, Hosung, et al.
Publicado: (2024)
Context-Sensitive Abstractions for Reinforcement Learning with Parameterized Actions
por: Nayyar, Rashmeet Kaur, et al.
Publicado: (2025)
por: Nayyar, Rashmeet Kaur, et al.
Publicado: (2025)
Causal Abstraction Learning based on the Semantic Embedding Principle
por: D'Acunto, Gabriele, et al.
Publicado: (2025)
por: D'Acunto, Gabriele, et al.
Publicado: (2025)
Realizable Abstractions: Near-Optimal Hierarchical Reinforcement Learning
por: Cipollone, Roberto, et al.
Publicado: (2025)
por: Cipollone, Roberto, et al.
Publicado: (2025)
Hide and Seek in Noise Labels: Noise-Robust Collaborative Active Learning with LLM-Powered Assistance
por: Yuan, Bo, et al.
Publicado: (2025)
por: Yuan, Bo, et al.
Publicado: (2025)
Neural Causal Abstractions
por: Xia, Kevin, et al.
Publicado: (2024)
por: Xia, Kevin, et al.
Publicado: (2024)
Learning under Temporal Label Noise
por: Nagaraj, Sujay, et al.
Publicado: (2024)
por: Nagaraj, Sujay, et al.
Publicado: (2024)
Parallel LLM Reasoning for Bias-Resilient, Robust Conceptual Abstraction
por: Adeseye, Aisvarya, et al.
Publicado: (2026)
por: Adeseye, Aisvarya, et al.
Publicado: (2026)
Decoupled Hierarchical Reinforcement Learning with State Abstraction for Discrete Grids
por: Xiao, Qingyu, et al.
Publicado: (2025)
por: Xiao, Qingyu, et al.
Publicado: (2025)
Learning with Expert Abstractions for Efficient Multi-Task Continuous Control
por: Jewett, Jeff, et al.
Publicado: (2025)
por: Jewett, Jeff, et al.
Publicado: (2025)
Learning Consistent Causal Abstraction Networks
por: D'Acunto, Gabriele, et al.
Publicado: (2026)
por: D'Acunto, Gabriele, et al.
Publicado: (2026)
On the Structural Limitations of Weight-Based Neural Adaptation and the Role of Reversible Behavioral Learning
por: Konduru, Pardhu Sri Rushi Varma
Publicado: (2026)
por: Konduru, Pardhu Sri Rushi Varma
Publicado: (2026)
Quantifying Itch and its Impact on Sleep Using Machine Learning and Radio Signals
por: Ouroutzoglou, Michail, et al.
Publicado: (2025)
por: Ouroutzoglou, Michail, et al.
Publicado: (2025)
Laziness, Barren Plateau, and Noise in Machine Learning
por: Liu, Junyu, et al.
Publicado: (2022)
por: Liu, Junyu, et al.
Publicado: (2022)
Ejemplares similares
-
CACTUS: a Comprehensive Abstraction and Classification Tool for Uncovering Structures
por: Gherardini, Luca, et al.
Publicado: (2023) -
Preservation of Feature Stability in Machine Learning Under Data Uncertainty for Decision Support in Critical Domains
por: Capała, Karol, et al.
Publicado: (2024) -
Optimisation Is Not What You Need
por: Ibias, Alfredo
Publicado: (2025) -
Knowledge Discovery using Unsupervised Cognition
por: Ibias, Alfredo, et al.
Publicado: (2024) -
Unsupervised Cognition
por: Ibias, Alfredo, et al.
Publicado: (2024)