Equivariant Learning

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3 papers in the last four weeks, down 50% on the four weeks before. 0.0% of all new papers.

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PI-AMFM: Permutation-Invariant Learning for Variable-Cardinality AM-FM Mode Decomposition in Biomedical Signal Analysis
Sep 30, 2026Youngsun Kong, Ki H. ChonDynamic Mode Decomposition Physiological Signals
Biomedical Engineering, University of Connecticut, Storrs, CT 06029, USA
WinoTS: Wavelet-based Self-Distillation for Time Series Models
Sep 30, 2026Noam Major, Kathy Razmadze, Yoli ShavitTime Series Wavelets
Bar-Ilan University, Ramat-Gan, Israel
Longer Records, Broader Invariance: The Hidden Scaling Problem in Longitudinal Contrastive Learning
Sep 29, 2026Rameen Mahmood, Xuhai "Orson" Xu, Zachary Beattie +2Longitudinal Data Contrastive Learning
New York University · Columbia University · Oregon Health & Science University
Transform-Aligned Learned Features for Lossy Point Cloud Attribute Compression
Sep 28, 2026Yueru Chen, Pengpeng Yu, Dingquan Li +3Point Clouds Rate-Distortion Theory
Pengcheng Laboratory, Shenzhen, China · Sun Yat-sen University, Shenzhen, China · Peking University, Shenzhen, China +1
PermuFormer: Multi-Task Pretraining for Permutation Representation in Algebraic Combinatorics
Sep 21, 2026Henry KvingePretraining Permutation
Pacific Northwest National Laboratory · University of Washington
$\mathbb{SL}(n)$ Representation Learning: An Intrinsic Mixed-Curvature Space with Higher Curvature Capacities and Deeper Order-Aware Composition
Sep 14, 2026Xingrun Li, Yusuke Mukuta, Xin Yang +2Representation Space Hyperbolic Learning
The University of Tokyo · Stanford University
Hierarchical and Permutation-Invariant Feature Transformation Learning via Policy-Guided Embedding Search
Sep 9, 2026Rui Liu, Tao Zhe, Yanyong Huang +5Tabular Learning Equivariant Learning
University of Kansas Lawrence, United States · Southwest University of Finance and Economics Chengdu, China · University of Wisconsin–Madison Madison, United States +3
Attributing Preprocessing Invariance in Spectral Foundation Models
Aug 14, 2026Dongjun Wei, Hongyi WuEquivariant Learning Raman
ESCP Business School, Paris · OpluxCare Tech Group Ltd. · The University of Hong Kong, Hong Kong
Equivariant learning of a transferable three-dimensional classical density functional
Aug 13, 2026Bingqing ChengDensity Functional Theory Statistical Physics
Department of Chemistry, UC Berkeley, California 94720, United States · Chemical Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California, 94720, United States · Bakar Institute of Digital Materials for the Planet, UC Berkeley, California 94720, United States
Dual-Manifold Geometry Guided Representation Learning: Adaptive Coupling between Kernel and Data Spaces
Aug 13, 2026Wencong Zhang, Yue Zhang, Meiyan Huang +2Representation Learning Equivariant Learning
School of Biomedical Engineering, Southern Medical University, China, Guangzhou 510515
Iterative Erasure Count Is Not an Affine-Invariant Concept Dimension
Aug 11, 2026Tingan Jin, Shuhang Dong, Haosong Li +1Intrinsic Dimensionality Concept Erasure
UCLA · Independent Researcher · Cal Poly Pomona
UPolarSQ: Polar Representation Learning for Optic Disc and Peripapillary Atrophy Segmentation and Quantification in Fundus Photographs
Aug 9, 2026Mengxian He, Yunyun sun, Ziyue Gao +3Fundus Images Vessel Segmentation
Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China · Capital Medical University, Beijing, China
Support Operation Factorization: Compositional Readout of Frozen Vision Encoders under Controlled Interventions
Aug 6, 2026Zhongyao Wang, Wanli Ouyang, Taoyong Cui +1Readout Frozen Encoder
Fudan University · MMLab, The Chinese University of Hong Kong · Department of Computer Science and Engineering, The Chinese University of Hong Kong
Unveiling Invariant and Transferable Latent Factors Across Heterogeneous Environments via ATLAS
Jul 20, 2026Yihong Gu, Katherine Liao, Tianxi CaiExploratory Factor Analysis Latent Variable
Harvard University
(MPO) $^2$ : Multivariate Polynomial Optimization based on Matrix Product Operators
Jul 17, 2026Niccolò Ciolli, Anders Vestergaard Nørskov, Michael Kastoryano +2Tensor Decomposition Matrix Multiplication
Any-Dimensional Learning by Sampling
Jul 8, 2026Eitan Levin, Venkat ChandrasekaranOptimal Sample Complexity Model Size
Department of Statistics University of Chicago Chicago, IL 60637 · Department of Computing and Mathematical Sciences Department of Electrical Engineering California Institute of Technology Pasadena, CA 91125
Domain Generalization via Text-Anchored Information Bottleneck
Jul 2, 2026Eunyi Lyou, Yunjeong Choi, Junho Lee +1Multimodal Domain Generalization Domain Invariance
Seoul National University, Seoul, Republic of Korea
BIFROST: Bridging Invariant Feature Representation for Observation-space Sim2Real Transfer
Jul 1, 2026Yunfu Deng, Josiah P. HannaSim-To-Real Reinforcement Learning Sim-To-Real Gap
Department of Computer Sciences, University of Wisconsin–Madison, Madison, WI 53706 USA
Data Augmentation: A Fourier Analysis Perspective
Jun 23, 2026Behrooz Tahmasebi, Melanie Weber, Stefanie JegelkaData Augmentation Equivariant Learning
Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA. · Technical University of Munich (CIT, MCML, MDSI) · MIT Computer Science and Artificial Intelligence Laboratory (CSAIL)
Is Spurious Correlation Removal Always Learnable?
Jun 11, 2026Yibo Zhou, Bo Li, Hai-Miao Hu +3Equivariant Learning Spurious Correlations
Beijing Key Laboratory of Digital Media, School of Computer Science and Engineering, Beihang University, Beijing 100191, China · State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing 100191, China · Hangzhou Innovation Institute of Beihang University, Hangzhou 310051, China +1
Vision-Encoder Behavioral Fingerprints of Image-to-Image Generative Models: A Training-Paradigm-Driven Taxonomy of Six Commercial APIs
Jun 10, 2026Hunter HillFingerprint Equivariant Learning
Cross Paraphrastic Invariance Learning for Hallucination Detection
Jun 6, 2026Shanshan Lin, Dongsheng Hong, Sibo Ju +3Large Language Model Hallucination Hallucination Detection
1Fuzhou University · 2Harbin Institute of Technology (Shenzhen) · 3The Hong Kong University of Science and Technology (Guangzhou)
Varifold Moment Invariants for Sustainable and Explainable Contour Feature Extraction
Jun 5, 2026G. Longari, J. -C. Alvarez Paiva, A. B. TumpachContours Feature Extraction
The Effect of Training Task Diversity on In-Context Learning through the Lens of Low-Dimensional Subspaces
Jun 5, 2026Soo Min Kwon, Alec S. Xu, Can Yaras +3In-Context Learning Equivariant Learning
Department of Electrical and Computer Engineering, University of Michigan · Department of Statistics, University of California, Davis
$p$ -adic Bi-Filtrations for Topological Machine Learning on Genomic Sequences
Jun 4, 2026Tirtharaj Dash, Gunja SachdevaGenome-Wide Association Study Topological Learning
Department of CS & IS, BITS Pilani, K K Birla Goa Campus, Zuarinagar, Goa 403726, India. · Department of Mathematics, BITS Pilani, K K Birla Goa Campus, Zuarinagar, Goa 403726, India.
Disentanglement-Based Equivariant Learning for Compositional VQA
Jun 1, 2026Zhou Du, Zhaoquan Yuan, Xiao Wu +1Knowledge-Based Visual Question Answering Equivariant Learning
School of Computing and Artificial Intelligence, Southwest Jiaotong University, Chengdu 611730, China, and also with Engineering Research Center of Sustainable Urban Intelligence Transportation, Ministry of Education, China · State Key Laboratory of Multimodal Artificial Intelligence Systems (MAIS), Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China, and with the School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 101408, China, and also with Peng Cheng Laboratory, ShenZhen 518055, China
LeAP: Learnable Adaptive Permutation for Feature Selection in Heterogeneous and Sparse Recommender Systems
May 31, 2026Yihong Huang, Chen Chu, Fei Chen +3Feature Selection Real-World Content Recommendation Problem
Bilibili Inc., Shanghai, China
Learning Transfers: Kan Extensions for Neural Invariants
May 30, 2026Luciano MelodiaEquivariant Learning Transfer Learning
Friedrich-Alexander Universität Erlangen-Nürnberg
Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic
May 30, 2026Pranav Darshan, Raghuveer Narayanan Rajesh, M Uttara KumariAutonomous Driving Perception 3D Object Detection
Department of Computer Science and Engineering RV College of Engineering, Bengaluru 560059, India · Department of Electronics and Communication Engineering RV College of Engineering, Bengaluru 560059, India
Learning Permutation-invariant Macroscopic Dynamics
May 29, 2026Zhichao Han, Mengyi Chen, Qianxiao LiParticle Dynamics Latent Dynamics
Institute for Functional Intelligent Materials, National University of Singapore · Department of Mathematics, National University of Singapore
Equivariant Latent Alignment via Flow Matching under Group Symmetries
May 29, 2026Sunghyun Kim, Jaehoon Hahm, Jeongwoo Shin +1Discriminative Congruence Transform Latent Flow
1Seoul National University, Seoul, Korea · University of Illinois Urbana-Champaign, Illinois, USA
Give it Space! Explicit Disentangling of Positional and Semantic Representations in Encoders
May 28, 2026Pierre-Antoine Lequeu, Camille Barboule, Benjamin PiwowarskiPositional Encoding Transformer Encoder
Sorbonne Université, CNRS, ISIR, Paris, France · Orange Innovation
On the Equivariant Learning of the $Q$ -tensor Order Parameter
May 26, 2026Julia Navarro, Mark WilkinsonEquivariant Neural Networks Equivariant Learning
Nottingham Trent University, UK · Berea College, USA
Learning Permutation from Structure Without Supervision
May 25, 2026Ran Eisenberg, Ofir LindenbaumPermutation Equivariant Learning
Faculty of Engineering, Bar-Ilan University, Ramat Gan, Israel. · Faculty of Engineering, Bar-Ilan
Factorize to Generalize: Retrieval-Guided Invariant-Dynamic Decomposition for Time Series Forecasting
May 24, 2026Jinjin Chi, Lei Feng, Lulu Zhang +6Zero-Shot Forecasting Time Series Forecasting
College of Computer Science and Technology, Jilin University, Changchun, China · College of Computing and Data Science, Nanyang Technological University, Singapore · City St George’s, University of London, London, United Kingdom +1
$\textit{BlockFormer}$ : Transformer-based inference from genomic contact maps
May 20, 2026Eloïse Touron, Pedro L. C. Rodrigues, Julyan Arbel +2Genome-Wide Association Study Flow Map
Univ. Grenoble Alpes, Inria CNRS, Grenoble INP, LJK, France · TIMC, Univ. Grenoble Alpes CNRS, Grenoble INP, France
Learning Unbiased Permutations via Flow Matching
May 16, 2026Yimeng Min, Carla P. GomesPermutation Conditional Flow Matching
Department of Computer Science Cornell University Ithaca, NY, USA
Stop Marginalizing My Dreams: Model Inversion via Laplace Kernel for Continual Learning
May 12, 2026Patryk Krukowski, Jacek Tabor, Przemysław Spurek +2Replay-Based Continual Learning Continual Learning
Jagiellonian University · IDEAS Research Institute
FeatMap: Understanding image manipulation in the feature space and its implications for feature space geometry
May 11, 2026Elias B. Krey, Nils Neukirch, Nils StrodthoffFeature Learning Equivariant Learning
Division AI4Health Carl von Ossietzky Universität Oldenburg Oldenburg, Germany
Birds of a Feather Flock Together: Background-Invariant Representations via Linear Structure in VLMs
May 11, 2026Youssef Zaazou, Mark ThomasVision Encoders Equivariant Learning
Independent Researcher
Operator-Guided Invariance Learning for Continuous Reinforcement Learning
May 7, 2026Zuyuan Zhang, Fei Xu Yu, Tian LanEquivariant Learning Action Space
The George Washington University
Beyond Rigid Geometries: The Spline-Pullback Metric for Universal Diffeomorphic SPD Representation Learning
May 6, 2026Tushar Das, Subrata Dutta, Sarmistha Neogy +1Splines Equivariant Learning
National Institute of Technology Jamshedpur · Jadavpur University · Machine Vision and Intelligence Lab National Institute of Technology Jamshedpur
DynaTab: Dynamic Feature Ordering as Neural Rewiring for High-Dimensional Tabular Data
May 5, 2026Al Zadid Sultan Bin Habib, Gianfranco Doretto, Donald A. AdjerohTabular Learning High-Dimensional
Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506, USA · Scientific Computing and Imaging Institute & Department of Biomedical Informatics, The University of Utah, Salt Lake City, UT 84112, USA
Towards Accelerated SCF Workflows with Equivariant Density-Matrix Learning and Analytic Refinement
Apr 29, 2026Zuriel Y. Yescas-Ramos, Andrés Álvarez-García, Huziel E. SaucedaQuantum Chemistry Equivariant Learning
Instituto de Física, Universidad Nacional Autónoma de México, Cd. de México C.P. 04510, Mexico
Learning to Solve the Quadratic Assignment Problem with Warm-Started MCMC Finetuning
Apr 22, 2026Yicheng Pan, Ruisong Zhou, Haijun Zou +2Repair-Assignment Problem Annealing
School of Mathematical Science, Peking University, Beijing 100871, China · State Key Laboratory of Mathematical Sciences, Institute of Computational Mathematics and Scientific/Engineering Computing, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China · Beijing International Center for Mathematical Research, Peking University, Beijing 100871, China
OSF: On Pre-training and Scaling of Sleep Foundation Models
Feb 27, 2026Zitao Shuai, Zongzhe Xu, David Yang +2Sleep Pretraining
University of California, Los Angeles · Emory University
Implicit Bias and Invariance: How Hopfield Networks Efficiently Learn Graph Orbits
Dec 16, 2025Michael Murray, Tenzin Chan, Kedar Karhadker +1Hopfield Networks Equivariant Learning
Mathematical Sciences, University of Bath · Department of Mathematics, UCLA · Algebraic
GraphIFE: Rethinking Graph Imbalance Node Classification via Invariant Learning
Sep 28, 2025Fanlong Zeng, Wensheng Gan, Kangjie Chen +1Imbalanced Classification Graph Representation Learning
School of Intelligent Systems Science and Engineering, Jinan University, Zhuhai 519070, China · School of Cybersecurity, Tianjin University, Tianjin 300354, China · University of Illinois Chicago, Chicago, USA
Permutation Learning with Only N Parameters: From SoftSort to Self-Organizing Gaussians
Mar 17, 2025Kai Uwe Barthel, Florian Barthel, Peter EisertFused Sinkhorn-Localized Similarity Equivariant Learning
Visual Computing Group · HTW Berlin · Berlin, Germany +2
Invariance Pair Guidance: Robustness to Spurious Correlations via Corrective Gradients
Feb 26, 2025Martin Surner, Abdelmajid Khelil, Ludwig BothmannAdversarial Training Covariate Shift
Institute for Data and Process Science, Landshut University of Applied Sciences, Landshut, Germany. · Computer Science Department, Landshut University of Applied Sciences, Landshut, Germany. · Department of Statistics, LMU Munich, Munich, Germany. +1
TIF: Learning Temporal Invariance in Android Malware Detectors
Feb 7, 2025Xinran Zheng, Shuo Yang, Edith C. H. Ngai +2Malware Equivariant Learning
University College London, London, UK · The University of Hong Kong, Hong Kong SAR, China · Columbia University, New York, USA
Invariant Graph Representations for Continuous-Time Dynamic Graphs Under Distribution Shifts
May 29, 2024Lanting Fang, Yulian Yang, Yawei Zhang +3Physics-Guided Diffusion Causal Discovery Methods
1Beijing Institue of Technology · Southeast University · Wuhan University
FEAT: A Linear-Complexity Foundation Model for Extremely Large Structured Data
Date pendingZhenghang Song, Tang Qian, Lu Chen +7Wireless Foundation Models Equivariant Learning
Zhejiang University · Ant Group · Aalborg University

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PI-AMFM: Permutation-Invariant Learning for Variable-Cardinality AM-FM Mode Decomposition in Biomedical Signal Analysis

Youngsun Kong, Ki H. Chon

Biomedical Engineering, University of Connecticut, Storrs, CT 06029, USA

Dynamic Mode Decomposition Physiological Signals Time-Frequency Frequency Neural Recordings Equivariant Learning+1

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Physiological recordings often contain nonstationary oscillatory components whose number and dynamics vary across signals. Amplitude- and frequency-modulated (AM-FM) representations are well suited to characterizing such dynamics and have shown broad utility in biomedical signal analysis. Recent approaches have incorporated neural networks to learn mode decomposition patterns from data, but component cardinality is often predefined or determined through separate stopping or selection mechanisms. We propose a permutation-invariant neural framework for variable-cardinality AM-FM mode decomposition (PI-AMFM). PI-AMFM combines a multiscale temporal encoder, Mamba backbone, and component-presence estimation, with permutation-invariant Hungarian matching during training. On synthetic AM-FM signals, PI-AMFM achieved lower decomposition, instantaneous-frequency, reconstruction, and mode-count errors than the compared methods while preserving the overall trajectory pattern in a crossing-chirp example. On photoplethysmographic recordings, recovered modes captured cardiac and respiratory dynamics despite training only on synthetic signals. These results support the feasibility of PI-AMFM for variable-cardinality decomposition of nonstationary biomedical signals.

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