Theory

Neural Active Learning with Performance Guarantees NeurIPS 2021 Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective ICLR 2021 Neuralizing Regular Expressions for Slot Filling EMNLP 2021 Neural Mechanics: Symmetry and Broken Conservation Laws in Deep Learning Dynamics ICLR 2021 Neural Natural Logic Inference for Interpretable Question Answering EMNLP 2021 Neural Response Interpretation Through the Lens of Critical Pathways CVPR 2021 Neural Splines: Fitting 3D Surfaces With Infinitely-Wide Neural Networks CVPR 2021 Neural-Symbolic Integration: A Compositional Perspective AAAI 2021 Neural Symplectic Form: Learning Hamiltonian Equations on General Coordinate Systems NeurIPS 2021 Never Go Full Batch (in Stochastic Convex Optimization) NeurIPS 2021 NOAHQA: Numerical Reasoning with Interpretable Graph Question Answering Dataset EMNLP 2021 Noether’s Learning Dynamics: Role of Symmetry Breaking in Neural Networks NeurIPS 2021 Noisy Gradient Descent Converges to Flat Minima for Nonconvex Matrix Factorization AISTATS 2021 Noisy Recurrent Neural Networks NeurIPS 2021 Non-Asymptotic Analysis for Two Time-scale TDC with General Smooth Function Approximation NeurIPS 2021 Non-asymptotic approximations of neural networks by Gaussian processes COLT 2021 Non-asymptotic Convergence of Adam-type Reinforcement Learning Algorithms under Markovian Sampling AAAI 2021 Non-asymptotic Error Bounds for Bidirectional GANs NeurIPS 2021 Non-attracting Regions of Local Minima in Deep and Wide Neural Networks JMLR 2021 Non-Autoregressive Electron Redistribution Modeling for Reaction Prediction ICML 2021 Nonseparable Symplectic Neural Networks ICLR 2021 Offline detection of change-points in the mean for stationary graph signals. AISTATS 2021 Of Moments and Matching: A Game-Theoretic Framework for Closing the Imitation Gap ICML 2021 On Calibration and Out-of-Domain Generalization NeurIPS 2021 One-pass Stochastic Gradient Descent in overparametrized two-layer neural networks AISTATS 2021