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Theory

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Papers

Identifiability Guarantees for Causal Disentanglement from Soft Interventions NIPS 2023
Optimization or Architecture: How to Hack Kalman Filtering NIPS 2023
Deep learning with kernels through RKHM and the Perron-Frobenius operator NIPS 2023
Structure of universal formulas NIPS 2023
Wide Neural Networks as Gaussian Processes: Lessons from Deep Equilibrium Models NIPS 2023
New Complexity-Theoretic Frontiers of Tractability for Neural Network Training NIPS 2023
Globally injective and bijective neural operators NIPS 2023
MADG: Margin-based Adversarial Learning for Domain Generalization NIPS 2023
Entropy-dissipation Informed Neural Network for McKean-Vlasov Type PDEs NIPS 2023
Going beyond persistent homology using persistent homology NIPS 2023
Sub-optimality of the Naive Mean Field approximation for proportional high-dimensional Linear Regression NIPS 2023
A graphon-signal analysis of graph neural networks NIPS 2023
Does a sparse ReLU network training problem always admit an optimum ? NIPS 2023
Calibrate and Boost Logical Expressiveness of GNN Over Multi-Relational and Temporal Graphs NIPS 2023
Analyzing Generalization of Neural Networks through Loss Path Kernels NIPS 2023
On Convergence of Polynomial Approximations to the Gaussian Mixture Entropy NIPS 2023
Functional Equivalence and Path Connectivity of Reducible Hyperbolic Tangent Networks NIPS 2023
Convolutional State Space Models for Long-Range Spatiotemporal Modeling NIPS 2023
Kernelized Reinforcement Learning with Order Optimal Regret Bounds NIPS 2023
Tracking Most Significant Shifts in Nonparametric Contextual Bandits NIPS 2023
Finite-Time Analysis of Single-Timescale Actor-Critic NIPS 2023
Distributionally Robust Linear Quadratic Control NIPS 2023
Connected Superlevel Set in (Deep) Reinforcement Learning and its Application to Minimax Theorems NIPS 2023
ReDS: Offline RL With Heteroskedastic Datasets via Support Constraints NIPS 2023
Exponential Lower Bounds for Fictitious Play in Potential Games NIPS 2023