Fast and Exact Enumeration of Deep Networks Partitions Regions
Fuente:
arXiv
Saved in:
| Main Authors: | Balestriero, Randall, LeCun, Yann |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Learning by Reconstruction Produces Uninformative Features For Perception
by: Balestriero, Randall, et al.
Published: (2024)
by: Balestriero, Randall, et al.
Published: (2024)
LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics
by: Balestriero, Randall, et al.
Published: (2025)
by: Balestriero, Randall, et al.
Published: (2025)
Gaussian Embeddings: How JEPAs Secretly Learn Your Data Density
by: Balestriero, Randall, et al.
Published: (2025)
by: Balestriero, Randall, et al.
Published: (2025)
LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels
by: Maes, Lucas, et al.
Published: (2026)
by: Maes, Lucas, et al.
Published: (2026)
Semantic Tube Prediction: Beating LLM Data Efficiency with JEPA
by: Huang, Hai, et al.
Published: (2026)
by: Huang, Hai, et al.
Published: (2026)
Variance Covariance Regularization Enforces Pairwise Independence in Self-Supervised Representations
by: Mialon, Grégoire, et al.
Published: (2022)
by: Mialon, Grégoire, et al.
Published: (2022)
LLM-JEPA: Large Language Models Meet Joint Embedding Predictive Architectures
by: Huang, Hai, et al.
Published: (2025)
by: Huang, Hai, et al.
Published: (2025)
Causal-JEPA: Learning World Models through Object-Level Latent Masking
by: Nam, Heejeong, et al.
Published: (2026)
by: Nam, Heejeong, et al.
Published: (2026)
Value-guided action planning with JEPA world models
by: Destrade, Matthieu, et al.
Published: (2025)
by: Destrade, Matthieu, et al.
Published: (2025)
Light-weight probing of unsupervised representations for Reinforcement Learning
by: Zhang, Wancong, et al.
Published: (2022)
by: Zhang, Wancong, et al.
Published: (2022)
ALLoRA: Adaptive Learning Rate Mitigates LoRA Fatal Flaws
by: Huang, Hai, et al.
Published: (2024)
by: Huang, Hai, et al.
Published: (2024)
Task Priors: Enhancing Model Evaluation by Considering the Entire Space of Downstream Tasks
by: Patel, Niket, et al.
Published: (2025)
by: Patel, Niket, et al.
Published: (2025)
No Location Left Behind: Measuring and Improving the Fairness of Implicit Representations for Earth Data
by: Cai, Daniel, et al.
Published: (2025)
by: Cai, Daniel, et al.
Published: (2025)
SAFE: A Novel Approach to AI Weather Evaluation through Stratified Assessments of Forecasts over Earth
by: Masi, Nick, et al.
Published: (2025)
by: Masi, Nick, et al.
Published: (2025)
Parallel Algorithms for Exact Enumeration of Deep Neural Network Activation Regions
by: Drammis, Sabrina, et al.
Published: (2024)
by: Drammis, Sabrina, et al.
Published: (2024)
What Drives Success in Physical Planning with Joint-Embedding Predictive World Models?
by: Terver, Basile, et al.
Published: (2025)
by: Terver, Basile, et al.
Published: (2025)
Deep Networks Always Grok and Here is Why
by: Humayun, Ahmed Imtiaz, et al.
Published: (2024)
by: Humayun, Ahmed Imtiaz, et al.
Published: (2024)
Blockwise Self-Supervised Learning at Scale
by: Siddiqui, Shoaib Ahmed, et al.
Published: (2023)
by: Siddiqui, Shoaib Ahmed, et al.
Published: (2023)
An Information-Theoretic Perspective on Variance-Invariance-Covariance Regularization
by: Shwartz-Ziv, Ravid, et al.
Published: (2023)
by: Shwartz-Ziv, Ravid, et al.
Published: (2023)
Occam's Razor for Self Supervised Learning: What is Sufficient to Learn Good Representations?
by: Ibrahim, Mark, et al.
Published: (2024)
by: Ibrahim, Mark, et al.
Published: (2024)
stable-worldmodel-v1: Reproducible World Modeling Research and Evaluation
by: Maes, Lucas, et al.
Published: (2026)
by: Maes, Lucas, et al.
Published: (2026)
Navigation World Models
by: Bar, Amir, et al.
Published: (2024)
by: Bar, Amir, et al.
Published: (2024)
On the Geometry of Deep Learning
by: Balestriero, Randall, et al.
Published: (2024)
by: Balestriero, Randall, et al.
Published: (2024)
Rectified LpJEPA: Joint-Embedding Predictive Architectures with Sparse and Maximum-Entropy Representations
by: Kuang, Yilun, et al.
Published: (2026)
by: Kuang, Yilun, et al.
Published: (2026)
Variance-Covariance Regularization Improves Representation Learning
by: Zhu, Jiachen, et al.
Published: (2023)
by: Zhu, Jiachen, et al.
Published: (2023)
Enumerating Safe Regions in Deep Neural Networks with Provable Probabilistic Guarantees
by: Marzari, Luca, et al.
Published: (2023)
by: Marzari, Luca, et al.
Published: (2023)
Transformers without Normalization
by: Zhu, Jiachen, et al.
Published: (2025)
by: Zhu, Jiachen, et al.
Published: (2025)
Learning from Reward-Free Offline Data: A Case for Planning with Latent Dynamics Models
by: Sobal, Vlad, et al.
Published: (2025)
by: Sobal, Vlad, et al.
Published: (2025)
Attention Sinks and Compression Valleys in LLMs are Two Sides of the Same Coin
by: Queipo-de-Llano, Enrique, et al.
Published: (2025)
by: Queipo-de-Llano, Enrique, et al.
Published: (2025)
Learning and Leveraging World Models in Visual Representation Learning
by: Garrido, Quentin, et al.
Published: (2024)
by: Garrido, Quentin, et al.
Published: (2024)
The Fair Language Model Paradox
by: Pinto, Andrea, et al.
Published: (2024)
by: Pinto, Andrea, et al.
Published: (2024)
Characterizing Large Language Model Geometry Helps Solve Toxicity Detection and Generation
by: Balestriero, Randall, et al.
Published: (2023)
by: Balestriero, Randall, et al.
Published: (2023)
Position: An Empirically Grounded Identifiability Theory Will Accelerate Self-Supervised Learning Research
by: Reizinger, Patrik, et al.
Published: (2025)
by: Reizinger, Patrik, et al.
Published: (2025)
Max-Affine Spline Insights Into Deep Network Pruning
by: You, Haoran, et al.
Published: (2021)
by: You, Haoran, et al.
Published: (2021)
Layer by Layer: Uncovering Hidden Representations in Language Models
by: Skean, Oscar, et al.
Published: (2025)
by: Skean, Oscar, et al.
Published: (2025)
Whole-Body Conditioned Egocentric Video Prediction
by: Bai, Yutong, et al.
Published: (2025)
by: Bai, Yutong, et al.
Published: (2025)
Introduction to Latent Variable Energy-Based Models: A Path Towards Autonomous Machine Intelligence
by: Dawid, Anna, et al.
Published: (2023)
by: Dawid, Anna, et al.
Published: (2023)
FastDINOv2: Frequency Based Curriculum Learning Improves Robustness and Training Speed
by: Zhang, Jiaqi, et al.
Published: (2025)
by: Zhang, Jiaqi, et al.
Published: (2025)
Why AI systems don't learn and what to do about it: Lessons on autonomous learning from cognitive science
by: Dupoux, Emmanuel, et al.
Published: (2026)
by: Dupoux, Emmanuel, et al.
Published: (2026)
Temporal Straightening for Latent Planning
by: Wang, Ying, et al.
Published: (2026)
by: Wang, Ying, et al.
Published: (2026)
Similar Items
-
Learning by Reconstruction Produces Uninformative Features For Perception
by: Balestriero, Randall, et al.
Published: (2024) -
LeJEPA: Provable and Scalable Self-Supervised Learning Without the Heuristics
by: Balestriero, Randall, et al.
Published: (2025) -
Gaussian Embeddings: How JEPAs Secretly Learn Your Data Density
by: Balestriero, Randall, et al.
Published: (2025) -
LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels
by: Maes, Lucas, et al.
Published: (2026) -
Semantic Tube Prediction: Beating LLM Data Efficiency with JEPA
by: Huang, Hai, et al.
Published: (2026)