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Theory

1072 directly classified papers

Papers per year

Papers

Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent From the Decision Boundary Perspective CVPR 2022
Demystifying the Neural Tangent Kernel From a Practical Perspective: Can It Be Trusted for Neural Architecture Search Without Training? CVPR 2022
How Much More Data Do I Need? Estimating Requirements for Downstream Tasks CVPR 2022
What You See is What You Get: Principled Deep Learning via Distributional Generalization NIPS 2022
Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures NIPS 2022
On the Double Descent of Random Features Models Trained with SGD NIPS 2022
Universality of Group Convolutional Neural Networks Based on Ridgelet Analysis on Groups NIPS 2022
Neural Differential Equations for Learning to Program Neural Nets Through Continuous Learning Rules NIPS 2022
Efficient MCMC Sampling with Dimension-Free Convergence Rate using ADMM-type Splitting JMLR 2022
Overparameterization of Deep ResNet: Zero Loss and Mean-field Analysis JMLR 2022
Foolish Crowds Support Benign Overfitting JMLR 2022
Mean-field Analysis of Piecewise Linear Solutions for Wide ReLU Networks JMLR 2022
Towards Bridging Sample Complexity and Model Capacity AAAI 2022
Zero Stability Well Predicts Performance of Convolutional Neural Networks AAAI 2022
The Effect of Manifold Entanglement and Intrinsic Dimensionality on Learning AAAI 2022
HNO: High-Order Numerical Architecture for ODE-Inspired Deep Unfolding Networks AAAI 2022
Sharp Analysis of Random Fourier Features in Classification AAAI 2022
Provable Guarantees for Understanding Out-of-Distribution Detection AAAI 2022
CC-CERT: A Probabilistic Approach to Certify General Robustness of Neural Networks AAAI 2022
Verification of Neural-Network Control Systems by Integrating Taylor Models and Zonotopes AAAI 2022
Does the Geometry of the Data Control the Geometry of Neural Predictions? (Student Abstract) AAAI 2022
Deep Representation Debiasing via Mutual Information Minimization and Maximization (Student Abstract) AAAI 2022
High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation NIPS 2022
Toward Equation of Motion for Deep Neural Networks: Continuous-time Gradient Descent and Discretization Error Analysis NIPS 2022
Annihilation of Spurious Minima in Two-Layer ReLU Networks NIPS 2022