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NeurIPS 2026Representation & contrastive learning

Structure-agnostic Causal Representation Learning

SaCRL jointly identifies causal structure and learns invariant representations via soft optimization over HSIC-based invariance violations without prior structural knowledge. It guarantees structure identification, invariance satisfaction, and out-of-distribution generalization while achieving state

Arman Behnam, Binghui Wang

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published Oct 1, 2026 · 0 citations

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arXivChinese University of Hong KongShanghai Artificial IntelligenceRepresentation & contrastive learning

MinkowskiPE: Minkowski Positional Encoding for Spatiotemporal Perception

MinkowskiPE applies Lorentz transformations via joint spacetime positional encoding to make attention depend only on relative displacement, improving molecular dynamics and video prediction with far fewer parameters.

Yuhao Li, Louie Hong Yao, Tianyi Shi, Hanqun Cao and 3 more

Published Sep 27, 2026 · 0 citations · ▲ 14 on Hugging Face

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arXivRepresentation & contrastive learning

JEPA-Anything: Learning Predictive Models across Different Worlds

JEPA-Anything uses orthogonal predictive factorization to learn cross-domain predictive models that outperform baselines in vision, biology, clinical, control, molecular, physical, and weather domains.

Taoyong Cui, Zhongyao Wang, Xinyue Xu, Weiyang Liu and 9 more

Published Sep 17, 2026 · 0 citations · ▲ 77 on Hugging Face · Code ★ 261

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NeurIPS 2026U Illinois Urbana-ChampaignMax Planck Institute for MathemaSolverXRepresentation & contrastive learning

SIEVE: Overcoming Topological Obstruction in Equivariant Self-Supervised Learning

Jongann Lee, Sun Woo Park, Yun Young Choi

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Massachusetts Institute of TechnMITUCSFRepresentation & contrastive learning

The Optimization Prior: Instilling depth for shallow networks, detail for coarse networks

Vighnesh Subramaniam, Boris Katz, Brian Cheung

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026GoogleU Southern CaliforniaGoogle ResearchUC San Diego / MilaRepresentation & contrastive learning

A Foundational Model System for Datacenter Machine Repairs

Yuanlin Wen, Elan S Markowitz, Zubo Gu, Sami Abu-El-Haija and 10 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U SurreyRepresentation & contrastive learning

Timing Is All You Need: SpikeCore, Learnable Delays, and Gain Control for Neuromorphic Classification

Mohsen Kamelian Rad, Sotiris Moschoyiannis, Roman Bauer

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026Northwest Polytechnical UniversiXi'an JiaotongRepresentation & contrastive learning

CASAM: Consistency-Anchored Sharpness-Aware Minimization for Improved Model Generalization

Chengli Tan, Tianyu Wang, Junmin Liu, Yong Xu

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Université de LiègeU LiègeU LiegeRepresentation & contrastive learning

Neuromodulated Constrained Autoencoders for Context-Dependent Manifold Learning

Jérôme Adriaens, Gustave Bainier, Guillaume Drion, Pierre Sacré

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026U Science and Technology of ChinHuazhong University of Science aInstitute of automation, ChineseRepresentation & contrastive learning

MemTailor: Hierarchical Memory-Augmented Multi-Expert Learning for Long-Tailed Recognition

Yuyang Sun, Senyang Su, Xiaotian Wang, Pengkun Wang and 1 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U TorontoBroad InstituteU Toronto & Vector InstituteU Toronto/Vector Institute/SickKRepresentation & contrastive learning

DynaSub: Adaptive Subgrouping for Scalable Representation Learning

Tina Behrouzi, Sana Tonekaboni, Rahul Krishnan, Anna Goldenberg

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026OffenburgInstitute for Machine Learning aRepresentation & contrastive learning

2D Spatial Reasoning with Adaptive Neural Cellular Automata

Martin Spitznagel, Janis Keuper

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026GriffithCity University of Hong KongRepresentation & contrastive learning

Permutation Sensitivity in t-SVD-based Multi-view Clustering

Jintian Ji, Yanjun Zhang, He Zhang, Leo Yu Zhang and 2 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026JinanRepresentation & contrastive learning

Learning Event-to-Field Operators Without Interpolation

xingyu sha

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026BoschRobert Bosch Research in North ARepresentation & contrastive learning

Balanced Multi-Task Learning from an Optimality-Gap Perspective

Ce Liu, Jianing Huang, HUANG Sicheng, Shu Liu and 2 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026California State University, NorU TrentoMPI for Intelligent Systems, TübRepresentation & contrastive learning

PVFormer: Proper Velocity Transformer for Stable and Scalable Hyperbolic Representation Learning

Xianglong Shi, Nicu Sebe, Bernhard Schölkopf, Ziheng Chen

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026DonghuaDonghua University, ShanghaiRepresentation & contrastive learning

Decentralized Coupled Representation Learning

Zilin Li, Weiwei Xu, Xuchun Tong, Xuanbo Lu and 2 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U Science and Technology of ChinRepresentation & contrastive learning

Distributed-Order Fractional Spiking Neural Network

Chengjie Ge, Yufeng Peng, Qiyu Kang, Xueyang Fu and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Texas A&MTexas A&MLambda, IncLambdaRepresentation & contrastive learning

Spin-Weighted Spherical Harmonics Enable Complete and Scalable E(3)-Equivariant Networks

Chenxing Liang, Yuchao Lin, Andrii Kryvenko, Wendi Yu and 4 more

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026U CambridgeRepresentation & contrastive learning

Robust Amortized Simulation-Based Inference via Learned Error Models

Matthew O'Callaghan, Kaisey Mandel, Gerard Gilmore

Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026SoutheastZhengzhouRepresentation & contrastive learning

Individuals Matter: Improving Deep Multi-View Clustering via Explicit Single-View Enhancement

Hanyang Li, Yanzheng Wang, Yaxin Hou, Zhengxing Jiao and 2 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026JinanDalian University of TechnologyRepresentation & contrastive learning

pyCD: A Unified Benchmark for Reliable Evaluation of Cognitive Diagnosis Models

Youheng Bai, Xueyi Li, Tengteng Cheng, Mingliang Hou and 3 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U SheffieldRepresentation & contrastive learning

Less Structure is More: Minimal Representations for Supervised Learning

Menghui Zhou, Vitaveska Lanfranchi, Po Yang

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026CWIUniversität zu LübeckRepresentation & contrastive learning

SpikingGamma: Temporally Precise Online SNN Training Through Smoothed Temporal Delays

Roel Koopman, Sebastian Otte, Sander Bohte

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026KU LeuvenRepresentation & contrastive learning

$\mathcal{P}$Torch: Narrowing the Gap Between Projection and Gradient-Based Learning

Jeff Cyuzuzo Jambé, Jan Quan, Panagiotis Patrinos

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Nanjing University of Science anRepresentation & contrastive learning

Memory-Driven Contrastive Embedding Enhancement for Fine-Grained Open-Set Semi-Supervised Learning

Yinan Han, Qing-Yuan Jiang

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026Victoria University of WellingtoRepresentation & contrastive learning

Deadline-Constrained Dynamic Workflow Scheduling Can be Cast as a Representation Learning Problem

Ya Shen, Gang Chen, Hui Ma, Mengjie Zhang

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Independent ResearcherRepresentation & contrastive learning

Layer Free-Riding in Forward-Forward Networks: Real, Repairable, but Not Accuracy-Dominant

Amirhossein Yousefiramandi

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026McGovern Institute for Brain ResRitsumeikanRepresentation & contrastive learning

Loop alignment: Self-organized Weight Transpose in Predictive Coding through Independent Hebbian Plasticity.

Kojiro Hirokane, Ryohei Ueno, Takashi Kitsukawa

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Beijing Normal University, SchooBeijing NormalRepresentation & contrastive learning

Gram-Calibrated Anchoring for Class-Incremental Learning

Qi Zhu, Ziang Gan, Libao Zhang

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026ServiceNow IncServiceNowIIIT HyderabadMila / Université de MontréalMontreal Institute for Learning Representation & contrastive learning

Do Enterprise Systems Need Learned World Models? The Importance of Context to Infer Dynamics

Jishnu S Nair, Patrice Bechard, Rishabh Maheshwary, SRAVAN RAMACHANDRAN and 13 more

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026China University of Mining and TChina University of Mining TechnRepresentation & contrastive learning

Beyond the Readout: Reservoir State Statistics for Model-Space Learning under Sparse Observations

Ao Chen, Yijing Lu, Pengpeng Chen

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Guangdong Provincial Laboratory Chinese Medicine Guangdong LaborMacau University of Science and Department of Computer Science aRepresentation & contrastive learning

Self-Supervised Reconstruction Knockoffs for Calibrated Unsupervised Feature Selection

HaiHui Huang, Dingkui Kang, Yanan Zhou, Yong Liang

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Sony AIVrije Universiteit AmsterdamFondazione Bruno KesslerU EdinburghRepresentation & contrastive learning

Where to Approximate in Neurosymbolic Inference?

Samy Badreddine, Emile van Krieken, Luciano Serafini, Antonio Vergari

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026StanfordPerceptaCornellRepresentation & contrastive learning

Refactoring Code Through Library Design

Žiga Kovačič, Justin Chiu, Celine Lee, Wenting Zhao and 1 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Massachusetts Institute of TechnMichigan StateMIT-IBM Watson AI LabRepresentation & contrastive learning

Dynamic Convolutions Improve Transformers

Oliver Sieberling, Bharat Runwal, Rameswar Panda, Yoon Kim

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026MITMassachusetts Institute of TechnInternational Centre for TheoretRepresentation & contrastive learning

The Marauder’s Map: Bézier Manifolds Reveal Hidden Surfaces for Model Merging and Ensembling

Abhiram Iyer, Mark T Harnett, Sarthak Chandra

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Gustave-EiffelEPFLEPFL - EPF LausanneRepresentation & contrastive learning

Recovering the Apresjan Hierarchy Using Linkage-Based Clustering

Maximilien Dreveton, Matthias Grossglauser, Daichi Kuroda, Patrick Thiran

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U SydneyThe University of SydneyRepresentation & contrastive learning

Approximation in Contrastive Representation Learning

Yuanfan Li, Zihan Zhang, Yiming Ying, Ding-Xuan Zhou

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U SydneyAdelaideShanghai NormalShanxiUniversity Of Technology SydneyRepresentation & contrastive learning

Resolution-Aware Structural Density Peak Clustering

Jie Yang, Hsiang-Ting Chen, Yan Ma, Xinyan Liang and 7 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026National Cheng KungAcademia SinicaRepresentation & contrastive learning

Distance-Dependent Connectivity Shapes Continual Learning by Synaptic-Resource-Delimited Separation of Neural Dynamics

CHIU-CHANG CHENG, Ching-Lung Hsu, Ya-Ning Chang, Chao-Hung Wang

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026RokuRepresentation & contrastive learning

k-th Order Deep Homomorphism Networks

Takanori Maehara

Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026HanyangOxfordRepresentation & contrastive learning

Saddle-to-Saddle Dynamics in Self-Supervised Shortcut Learning

Juhwan Kim, yoonsoo nam, Sungyoon Lee

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026SpotlightImperial College LondonRepresentation & contrastive learning

Casper: A Projection-Based Neurosymbolic Layer for Scalable & Guaranteed Constraint Satisfaction

Lohith Konathala, Luca Andolfi, Eleonora Giunchiglia

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026U Electronic Science and TechnolTsinghuaFudanRepresentation & contrastive learning

SpikeSSL: A Universal Spike Inference Framework with Dynamics-Informed State-Space Layers

Chenghao Yue, Siming Xing, shuran liu, Angran Li and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026ChongqingchongqingRepresentation & contrastive learning

Learning Joint Semantic-Geometric Uncertainty for Structured Prediction with Closed-Loop Calibration

Bohan Li, Rui Leng, Qi Ma, Shaoyuan Mo and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Toronto MetropolitanRepresentation & contrastive learning

The Structural Bias of $\ell_2$-Regularized Cross-Entropy Heads in Class-Incremental Learning: Characterization, Limits, and a Gauge-Anchoring Fix

Milad Khademi Nori, Guanghui Wang

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026U CambridgeRepresentation & contrastive learning

Scaling Causal Reasoning with Increasingly Complex Causal Simulators

Nicolás Astorga, Anita Kriz, Mihaela van der Schaar

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026KAISTKorea Advanced Institute of ScieKorea Advanced Institute of ScieRepresentation & contrastive learning

BabyTheorist: A Benchmark for Learning to Theorize the World from Observation Alone

Doojin Baek, Junyeob Baek, Mingyu Jo, Hosung Lee and 3 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U California, BerkeleyUni Tübingen / MPI-ISU California at BerkeleyTechnische Universität DarmstadtRepresentation & contrastive learning

What Is Worth Representing? Representational Empowerment for Continual Model Construction

Fei Dai, Hanqi Zhou, Alison Gopnik, Charley M Wu

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Massachusetts Institute of TechnCMUVirginia Polytechnic Institute aCarnegie MellonRepresentation & contrastive learning

Position: Neurosymbolic AI is a strong technical foundation for trustworthy, deployable AI by design

Chandler Squires, Yaqi Xie, Simon Stepputtis, Katia Sycara and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U PennsylvaniaRepresentation & contrastive learning

Position: The Road to Generalizable Neuro-Symbolic Learning Should be Paved with Foundation Models

Adam Stein, Aaditya Naik, Neelay Velingker, Mayur Naik and 1 more

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026Queen'sQueensQueen’sRepresentation & contrastive learning

A Theoretical Bridge Between Long-Tailed Recognition and Continual Learning

Mahdiyar Molahasani, Michael Greenspan, Ali Etemad

Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026Tel AvivOpen University of IsraelRepresentation & contrastive learning

Semantic Concept Steering Breaks the Explanation Drift Loop in Continual Learning

Yehonatan Elisha, Oren Barkan, Noam Koenigstein

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026YonseiRepresentation & contrastive learning

Not All Routing Drift Is Harmful: Trust-Region Projection for Class-Incremental Learning

Tae-Hwan Kim, Sung-Bae Cho

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Carnegie MellonRepresentation & contrastive learning

Projection Learning: A Principled Way to Overcome Memorization in Distribution Learning

Lin Chen, Dejan Slepcev

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026TechnionTechnion / NVIDIA ResearchRepresentation & contrastive learning

Positional Encoding Is All You Need For Scalable Equivariance Constraint Relaxation

Hagay Michaeli, Haggai Maron, Daniel Soudry

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026Institute of Theoretical and AppAGH University of Science and TeAmericanU RochesterRepresentation & contrastive learning

Lost or Hidden? A Concept-Level Forgetting in Supervised Continual Learning

Katarzyna Filus, Kamil Faber, Roberto Corizzo, Christopher Kanan

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026KoreaTelecom Paris, IP ParisKorea Institute of Science and TRepresentation & contrastive learning

Rethinking Attention in Depth for Operator Learning

Jaehyeon Lee, Kiwon Um, JungHyun Han, Min-Koo Kang

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026Universität BernU BernU Bern and HeidelbergDepartment of Physiology, UniverRepresentation & contrastive learning

K-prop: Deep Online Learning by Backpropagating Temporal Kernels

Bingkun Liu, Paul Haider, Federico Benitez, Mihai A. Petrovici and 1 more

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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