Dense associative memory for Gaussian distributions
Fuente:
arXiv
Saved in:
| Main Authors: | Tankala, Chandan, Balasubramanian, Krishnakumar |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Finite-Particle Convergence Rates for Conservative and Non-Conservative Drifting Models
by: Balasubramanian, Krishnakumar
Published: (2026)
by: Balasubramanian, Krishnakumar
Published: (2026)
A Quantitative Characterization of Forgetting in Post-Training
by: Balasubramanian, Krishnakumar, et al.
Published: (2026)
by: Balasubramanian, Krishnakumar, et al.
Published: (2026)
Total Variation Rates for Riemannian Flow Matching
by: Guan, Yunrui, et al.
Published: (2026)
by: Guan, Yunrui, et al.
Published: (2026)
Transformers Handle Endogeneity in In-Context Linear Regression
by: Liang, Haodong, et al.
Published: (2024)
by: Liang, Haodong, et al.
Published: (2024)
Differentially Private Two-Stage Gradient Descent for Instrumental Variable Regression
by: Liang, Haodong, et al.
Published: (2025)
by: Liang, Haodong, et al.
Published: (2025)
Finite-Dimensional Gaussian Approximation for Deep Neural Networks: Universality in Random Weights
by: Balasubramanian, Krishnakumar, et al.
Published: (2025)
by: Balasubramanian, Krishnakumar, et al.
Published: (2025)
Multivariate Gaussian Approximation for Random Forest via Region-based Stabilization
by: Shi, Zhaoyang, et al.
Published: (2024)
by: Shi, Zhaoyang, et al.
Published: (2024)
Gaussian random field approximation via Stein's method with applications to wide random neural networks
by: Balasubramanian, Krishnakumar, et al.
Published: (2023)
by: Balasubramanian, Krishnakumar, et al.
Published: (2023)
A Separation in Heavy-Tailed Sampling: Gaussian vs. Stable Oracles for Proximal Samplers
by: He, Ye, et al.
Published: (2024)
by: He, Ye, et al.
Published: (2024)
Riemannian Proximal Sampler for High-accuracy Sampling on Manifolds
by: Guan, Yunrui, et al.
Published: (2025)
by: Guan, Yunrui, et al.
Published: (2025)
Statistical Inference for Linear Functionals of Online Least-squares SGD when $t \gtrsim d^{1+δ}$
by: Agrawalla, Bhavya, et al.
Published: (2025)
by: Agrawalla, Bhavya, et al.
Published: (2025)
Meta-Learning with Generalized Ridge Regression: High-dimensional Asymptotics, Optimality and Hyper-covariance Estimation
by: Jin, Yanhao, et al.
Published: (2024)
by: Jin, Yanhao, et al.
Published: (2024)
Nonsmooth Nonparametric Regression via Fractional Laplacian Eigenmaps
by: Shi, Zhaoyang, et al.
Published: (2024)
by: Shi, Zhaoyang, et al.
Published: (2024)
Gaussian and Bootstrap Approximation for Matching-based Average Treatment Effect Estimators
by: Shi, Zhaoyang, et al.
Published: (2024)
by: Shi, Zhaoyang, et al.
Published: (2024)
Improved Finite-Particle Convergence Rates for Stein Variational Gradient Descent
by: Banerjee, Sayan, et al.
Published: (2024)
by: Banerjee, Sayan, et al.
Published: (2024)
Finite-Particle Rates for Regularized Stein Variational Gradient Descent
by: He, Ye, et al.
Published: (2026)
by: He, Ye, et al.
Published: (2026)
Identifiability of Potentially Degenerate Gaussian Mixture Models With Piecewise Affine Mixing
by: Xu, Danru, et al.
Published: (2026)
by: Xu, Danru, et al.
Published: (2026)
Large-Step Training Dynamics of a Two-Factor Linear Transformer Model
by: Balasubramanian, Krishnakumar
Published: (2026)
by: Balasubramanian, Krishnakumar
Published: (2026)
Statistical Inference for Linear Functionals of Online SGD in High-dimensional Linear Regression
by: Agrawalla, Bhavya, et al.
Published: (2023)
by: Agrawalla, Bhavya, et al.
Published: (2023)
High-dimensional scaling limits and fluctuations of online least-squares SGD with smooth covariance
by: Balasubramanian, Krishnakumar, et al.
Published: (2023)
by: Balasubramanian, Krishnakumar, et al.
Published: (2023)
Beyond Propagation of Chaos: A Stochastic Algorithm for Mean Field Optimization
by: Tankala, Chandan, et al.
Published: (2025)
by: Tankala, Chandan, et al.
Published: (2025)
Efficient Knowledge Distillation via Curriculum Extraction
by: Gupta, Shivam, et al.
Published: (2025)
by: Gupta, Shivam, et al.
Published: (2025)
Risk Analysis and Design Against Adversarial Actions
by: Campi, Marco C., et al.
Published: (2025)
by: Campi, Marco C., et al.
Published: (2025)
Navigating the Exploration-Exploitation Tradeoff in Inference-Time Scaling of Diffusion Models
by: Su, Xun, et al.
Published: (2025)
by: Su, Xun, et al.
Published: (2025)
A Theory of the Mechanics of Information: Generalization Through Measurement of Uncertainty (Learning is Measuring)
by: Hazard, Christopher J., et al.
Published: (2025)
by: Hazard, Christopher J., et al.
Published: (2025)
Solving a Research Problem in Mathematical Statistics with AI Assistance
by: Dobriban, Edgar
Published: (2025)
by: Dobriban, Edgar
Published: (2025)
Cross-regularization: Adaptive Model Complexity through Validation Gradients
by: Brito, Carlos Stein
Published: (2025)
by: Brito, Carlos Stein
Published: (2025)
Residual Feature Integration is Sufficient to Prevent Negative Transfer
by: Xu, Yichen, et al.
Published: (2025)
by: Xu, Yichen, et al.
Published: (2025)
Towards a Sharp Analysis of Offline Policy Learning for $f$-Divergence-Regularized Contextual Bandits
by: Zhao, Qingyue, et al.
Published: (2025)
by: Zhao, Qingyue, et al.
Published: (2025)
On the Statistical Capacity of Deep Generative Models
by: Tam, Edric, et al.
Published: (2025)
by: Tam, Edric, et al.
Published: (2025)
Provable Robust Overfitting Mitigation in Wasserstein Distributionally Robust Optimization
by: Liu, Shuang, et al.
Published: (2025)
by: Liu, Shuang, et al.
Published: (2025)
When Can We Reuse a Calibration Set for Multiple Conformal Predictions?
by: Balinsky, A. A., et al.
Published: (2025)
by: Balinsky, A. A., et al.
Published: (2025)
How Particle-System Random Batch Methods Enhance Graph Transformer: Memory Efficiency and Parallel Computing Strategy
by: Liu, Hanwen, et al.
Published: (2025)
by: Liu, Hanwen, et al.
Published: (2025)
On the Provable Performance Guarantee of Efficient Reasoning Models
by: Zeng, Hao, et al.
Published: (2025)
by: Zeng, Hao, et al.
Published: (2025)
What is causal about causal models and representations?
by: Jørgensen, Frederik Hytting, et al.
Published: (2025)
by: Jørgensen, Frederik Hytting, et al.
Published: (2025)
Generalizability of Neural Networks Minimizing Empirical Risk Based on Expressive Ability
by: Yu, Lijia, et al.
Published: (2025)
by: Yu, Lijia, et al.
Published: (2025)
The Good, the Bad, and the Sampled: a No-Regret Approach to Safe Online Classification
by: Baharav, Tavor Z., et al.
Published: (2025)
by: Baharav, Tavor Z., et al.
Published: (2025)
Enjoying Non-linearity in Multinomial Logistic Bandits: A Minimax-Optimal Algorithm
by: Boudart, Pierre, et al.
Published: (2025)
by: Boudart, Pierre, et al.
Published: (2025)
On the Geometry of Receiver Operating Characteristic and Precision-Recall Curves
by: Sameni, Reza
Published: (2025)
by: Sameni, Reza
Published: (2025)
A Computational Theory for Efficient Mini Agent Evaluation with Causal Guarantees
by: Yan, Hedong
Published: (2025)
by: Yan, Hedong
Published: (2025)
Similar Items
-
Finite-Particle Convergence Rates for Conservative and Non-Conservative Drifting Models
by: Balasubramanian, Krishnakumar
Published: (2026) -
A Quantitative Characterization of Forgetting in Post-Training
by: Balasubramanian, Krishnakumar, et al.
Published: (2026) -
Total Variation Rates for Riemannian Flow Matching
by: Guan, Yunrui, et al.
Published: (2026) -
Transformers Handle Endogeneity in In-Context Linear Regression
by: Liang, Haodong, et al.
Published: (2024) -
Differentially Private Two-Stage Gradient Descent for Instrumental Variable Regression
by: Liang, Haodong, et al.
Published: (2025)