Universal approximations of invariant maps by neural networks

26 April 2018

Papers citing "Universal approximations of invariant maps by neural networks"

50 / 134 papers shown

Title
Lie Group Symmetry Discovery and Enforcement Using Vector Fields Ben Shaw Sasidhar Kunapuli Abram Magner Kevin R. Moon 27 0 0 13 May 2025
Permutation Equivariant Neural Networks for Symmetric Tensors Edward Pearce-Crump 50 0 0 14 Mar 2025
Rethinking Addressing in Language Models via Contexualized Equivariant Positional Encoding Jiajun Zhu Peihao Wang Ruisi Cai Jason D. Lee Pan Li Zhilin Wang KELM 45 1 0 03 Jan 2025
Stability of sorting based embeddings Radu Balan Efstratios Tsoukanis Matthias Wellershoff 23 2 0 07 Oct 2024
Towards Better Generalization: Weight Decay Induces Low-rank Bias for Neural Networks Ke Chen Chugang Yi Haizhao Yang MLT 21 0 0 03 Oct 2024
Variational Source-Channel Coding for Semantic Communication Yulong Feng Jing Xu Liujun Hu Guanghui Yu Xiangyang Duan 23 0 0 26 Sep 2024
Decomposition of Equivariant Maps via Invariant Maps: Application to Universal Approximation under Symmetry Akiyoshi Sannai Yuuki Takai Matthieu Cordonnier 178 0 0 25 Sep 2024
Variational Inference Failures Under Model Symmetries: Permutation Invariant Posteriors for Bayesian Neural Networks Yoav Gelberg Tycho F. A. van der Ouderaa Mark van der Wilk Y. Gal AAML 37 4 0 10 Aug 2024
Scale Equivariant Graph Metanetworks Ioannis Kalogeropoulos Giorgos Bouritsas Yannis Panagakis 44 6 0 15 Jun 2024
Separation Power of Equivariant Neural Networks Marco Pacini Xiaowen Dong Bruno Lepri G. Santin 31 0 0 13 Jun 2024
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency Yuchao Lin Jacob Helwig Shurui Gui Shuiwang Ji 42 7 0 11 Jun 2024
Learning Long Range Dependencies on Graphs via Random Walks Dexiong Chen Till Hendrik Schulz Karsten Borgwardt 34 2 0 05 Jun 2024
Learning equivariant tensor functions with applications to sparse vector recovery Wilson Gregory Josué Tonelli-Cueto Nicholas F. Marshall Andrew S. Lee Soledad Villar 39 1 0 03 Jun 2024
A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction Keqiang Yan Alexandra Saxton Xiaofeng Qian Xiaoning Qian Shuiwang Ji 39 6 0 03 Jun 2024
Symmetries in Overparametrized Neural Networks: A Mean-Field View Javier Maass Martínez Joaquin Fontbona FedML MLT 50 2 0 30 May 2024
Equivariant Frames and the Impossibility of Continuous Canonicalization Nadav Dym Hannah Lawrence Jonathan W. Siegel 41 17 0 25 Feb 2024
A unified Fourier slice method to derive ridgelet transform for a variety of depth-2 neural networks Sho Sonoda Isao Ishikawa Masahiro Ikeda 41 4 0 25 Feb 2024
G-RepsNet: A Fast and General Construction of Equivariant Networks for Arbitrary Matrix Groups Sourya Basu Suhas Lohit Matthew Brand 42 0 0 23 Feb 2024
Which Frequencies do CNNs Need? Emergent Bottleneck Structure in Feature Learning Yuxiao Wen Arthur Jacot 58 6 0 12 Feb 2024
Approximation Rates and VC-Dimension Bounds for (P)ReLU MLP Mixture of Experts Anastasis Kratsios Haitz Sáez de Ocáriz Borde Takashi Furuya Marc T. Law MoE 41 1 0 05 Feb 2024
A Characterization Theorem for Equivariant Networks with Point-wise Activations Marco Pacini Xiaowen Dong Bruno Lepri G. Santin 44 2 0 17 Jan 2024
Neural Collapse for Cross-entropy Class-Imbalanced Learning with Unconstrained ReLU Feature Model Hien Dang Tho Tran Tan Minh Nguyen Nhat Ho 22 11 0 04 Jan 2024
Expressive Sign Equivariant Networks for Spectral Geometric Learning Derek Lim Joshua Robinson Stefanie Jegelka Haggai Maron 71 16 0 04 Dec 2023
$Learning Polynomial Problems with $SL(2,\mathbb{R})$ Equivariance$ Learning Polynomial Problems with $SL(2,\mathbb{R})$ Equivariance Hannah Lawrence Mitchell Tong Harris 27 1 0 04 Dec 2023
Machine Learning for the identification of phase-transitions in interacting agent-based systems: a Desai-Zwanzig example N. Evangelou Dimitrios G. Giovanis George A. Kevrekidis G. Pavliotis Ioannis G. Kevrekidis 11 0 0 29 Oct 2023
Efficient Model-Agnostic Multi-Group Equivariant Networks Razan Baltaji Sourya Basu L. Varshney 32 1 0 14 Oct 2023
Improving Equivariance in State-of-the-Art Supervised Depth and Normal Predictors Yuanyi Zhong Anand Bhattad Yu-Xiong Wang David Forsyth MDE 26 2 0 28 Sep 2023
Neural approximation of Wasserstein distance via a universal architecture for symmetric and factorwise group invariant functions Samantha Chen Yusu Wang 20 3 0 01 Aug 2023
Polynomial Width is Sufficient for Set Representation with High-dimensional Features Peihao Wang Shenghao Yang Shu Li Zhangyang Wang Pan Li 19 3 0 08 Jul 2023
Sumformer: Universal Approximation for Efficient Transformers Silas Alberti Niclas Dern L. Thesing Gitta Kutyniok 19 16 0 05 Jul 2023
Learning Lie Group Symmetry Transformations with Neural Networks Alex Gabel Victoria G Klein Riccardo Valperga J. Lamb K. Webster Rick Quax E. Gavves 27 5 0 04 Jul 2023
Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance Jinwoo Kim Tien Dat Nguyen Ayhan Suleymanzade Hyeokjun An Seunghoon Hong 50 23 0 05 Jun 2023
Universal approximation with complex-valued deep narrow neural networks Paul Geuchen Thomas Jahn Hannes Matt 13 3 0 26 May 2023
Efficient Equivariant Transfer Learning from Pretrained Models Sourya Basu Pulkit Katdare P. Sattigeri Vijil Chenthamarakshan Katherine Driggs Campbell Payel Das L. Varshney 40 7 0 17 May 2023
FAENet: Frame Averaging Equivariant GNN for Materials Modeling Alexandre Duval Victor Schmidt A. Garcia Santiago Miret Fragkiskos D. Malliaros Yoshua Bengio David Rolnick 34 55 0 28 Apr 2023
The Exact Sample Complexity Gain from Invariances for Kernel Regression B. Tahmasebi Stefanie Jegelka 28 17 0 24 Mar 2023
Anti-symmetric Barron functions and their approximation with sums of determinants Nilin Abrahamsen Lin Lin 25 4 0 22 Mar 2023
A General Theory of Correct, Incorrect, and Extrinsic Equivariance Dian Wang Xu Zhu Jung Yeon Park Mingxi Jia Guanang Su Robert W. Platt Robin G. Walters 26 13 0 08 Mar 2023
A Brief Survey on the Approximation Theory for Sequence Modelling Hao Jiang Qianxiao Li Zhong Li Shida Wang AI4TS 30 12 0 27 Feb 2023
Invariant Layers for Graphs with Nodes of Different Types Dmitry Rybin Ruoyu Sun Zhimin Luo 23 0 0 27 Feb 2023
Equivariant and Steerable Neural Networks: A review with special emphasis on the symmetric group Patrick Krüger Hanno Gottschalk 21 1 0 08 Jan 2023
Invariance-Aware Randomized Smoothing Certificates Jan Schuchardt Stephan Günnemann AAML 28 5 0 25 Nov 2022
On the Universal Approximation Property of Deep Fully Convolutional Neural Networks Ting-Wei Lin Zuowei Shen Qianxiao Li 34 4 0 25 Nov 2022
Equivariance with Learned Canonicalization Functions Sekouba Kaba Arnab Kumar Mondal Yan Zhang Yoshua Bengio Siamak Ravanbakhsh 44 61 0 11 Nov 2022
On the Approximation and Complexity of Deep Neural Networks to Invariant Functions Gao Zhang Jin-Hui Wu Shao-Qun Zhang 16 0 0 27 Oct 2022
A tradeoff between universality of equivariant models and learnability of symmetries Vasco Portilheiro 32 2 0 17 Oct 2022
Theory for Equivariant Quantum Neural Networks Quynh T. Nguyen Louis Schatzki Paolo Braccia Michael Ragone Patrick J. Coles F. Sauvage Martín Larocca M. Cerezo 37 88 0 16 Oct 2022
Equi-Tuning: Group Equivariant Fine-Tuning of Pretrained Models Sourya Basu P. Sattigeri K. Ramamurthy Vijil Chenthamarakshan Kush R. Varshney L. Varshney Payel Das 8 18 0 13 Oct 2022
Deep Invertible Approximation of Topologically Rich Maps between Manifolds Michael Puthawala Matti Lassas Ivan Dokmanić Pekka Pankka Maarten V. de Hoop MedIm 26 0 0 02 Oct 2022
Machine learning and invariant theory Ben Blum-Smith Soledad Villar AI4CE 33 16 0 29 Sep 2022