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Neural Networks

11,300 papers

Papers per year

Papers

Long Sequence Hopfield Memory NIPS 2023
Sparse Deep Learning for Time Series Data: Theory and Applications NIPS 2023
A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance Estimation NIPS 2023
Structure of universal formulas NIPS 2023
A General Framework for Equivariant Neural Networks on Reductive Lie Groups NIPS 2023
Provable Guarantees for Neural Networks via Gradient Feature Learning NIPS 2023
FABind: Fast and Accurate Protein-Ligand Binding NIPS 2023
Causes and Effects of Unanticipated Numerical Deviations in Neural Network Inference Frameworks NIPS 2023
How do Minimum-Norm Shallow Denoisers Look in Function Space? NIPS 2023
Residual Alignment: Uncovering the Mechanisms of Residual Networks NIPS 2023
Implicit Bias of (Stochastic) Gradient Descent for Rank-1 Linear Neural Network NIPS 2023
Enhancing Adaptive History Reserving by Spiking Convolutional Block Attention Module in Recurrent Neural Networks NIPS 2023
UE4-NeRF:Neural Radiance Field for Real-Time Rendering of Large-Scale Scene NIPS 2023
Improving Compositional Generalization using Iterated Learning and Simplicial Embeddings NIPS 2023
Scaling MLPs: A Tale of Inductive Bias NIPS 2023
MeCo: Zero-Shot NAS with One Data and Single Forward Pass via Minimum Eigenvalue of Correlation NIPS 2023
Are aligned neural networks adversarially aligned? NIPS 2023
Approximation-Generalization Trade-offs under (Approximate) Group Equivariance NIPS 2023
Clifford Group Equivariant Neural Networks NIPS 2023
Sampling weights of deep neural networks NIPS 2023
Riemannian Residual Neural Networks NIPS 2023
Leveraging the two-timescale regime to demonstrate convergence of neural networks NIPS 2023
Exploring Loss Functions for Time-based Training Strategy in Spiking Neural Networks NIPS 2023
Volume Feature Rendering for Fast Neural Radiance Field Reconstruction NIPS 2023
Deep Contract Design via Discontinuous Networks NIPS 2023