Topological Representation Learning

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10 papers in the last four weeks, against 1 the four weeks before. 0.1% of all new papers.

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TIRA: Tumor Immune Representation Adaptation for Zero-Shot Cross-Cancer MSI and TMB Prediction
Oct 7, 2026Dasari Naga RajuClinical Prediction Domain Generalization
Independent Researcher, Andhra Pradesh, India
Mathematical Invariant-Enabled Topological Neural Networks for Molecular and Materials Property Prediction
Oct 6, 2026Yiming Ren, Xiang Liu, Mustafa Hajij +2Materials Property Prediction Molecular Property Prediction
Department of Mathematics, University of Georgia, Athens, GA 30602, USA. · Department of Data Science, University of San Francisco, CA 94117, USA. · Department of Computer Science and Technology, Cambridge University, Cambridge, United Kingdom. +2
Operational Abstractions of Neural Network Concepts via Topological Representations
Oct 4, 2026Mathieu Pont, Christoph GarthDisentangled Representation Learning Model Editing
RPTU Kaiserslautern-Landau RPTU Kaiserslautern-Landau Kaiserslautern, Germany
Higher-Order Molecular Grammars for Generative and Foundation Models in Chemistry
Oct 1, 2026Yiming Huang, Yujie Zeng, Vijay Prakash Dwivedi +4Graph Representation Learning Molecular Generation
Department of Computing, Imperial College London, London, UK · School of Electronic Engineering and Computer Science, Queen Mary University of London, London, UK · Department of Computer Science, Stanford University, Stanford, CA, USA +1
Graph Representation via Elements of Discrete Morse and Cobordism Theories
Oct 1, 2026Jennifer Rozenblit, Chenguang Yang, Yuxin Liu +2Diffusion Model Guidance Topological Representation Learning
Department of Mathematics; University of Texas, Austin · Department of Statistics; University of California, Riverside · Department of Statistics; Virginia Tech
Higher-Order Positional Encodings for Graph Representation Learning
Oct 1, 2026Caleb Stam, Aagrim Hoysal, Sanjukta KrishnagopalGraph Representation Learning Positional Encoding
University of California, Santa Barbara
Topological Signatures of Cyber-Attack Classes in Natural Visibility Graph Representations of Network Traffic
Sep 22, 2026Ali Melih Kanca, Ilker TurkerNetwork Intrusion Detection Graph Classification
Department of Computer Engineering, Faculty of Computing and Informatics Sciences, Karabuk University, Karabuk, Türkiye
Signed Graph Pre-Training and Prompt Learning
Sep 22, 2026Zihan Mei, Rong Pan, Yuzhou Chen +1Prompt Learning Graph Representation Learning
Arizona State University · University of California, Riverside
CableVLA: Simulation-Privileged Global-Local Representation Learning for Cable Routing
Sep 22, 2026Zhifei Teng, Bo Feng, Xiang Zou +4Visuo-Tactile Representation Learning Sim-to-Real Transfer
State Key Laboratory of Intelligent Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China. · School of Mathematics, Harbin Institute of Technology, Harbin, China.
Repurposing Unified Topological Signatures for Graph Representation Learning
Sep 15, 2026Sanyam Sanjay Jain, Anshika Krishnatray, Aditya Sharma +1Graph Representation Learning GNN Expressivity
BITS Pilani, India
Synergistic Fusion of Topological Structure and Temporal Semantics of Mobility for Urban Region Embedding
Sep 8, 2026Namwoo Kim, Jeeyun Chang, Kanghoon Lee +1Feature Interaction Modeling Geospatial Representation Learning
Urban AI Institute, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea · Graduate School of Data Science, KAIST, Daejeon, Republic of Korea · Department of Industrial Engineering and Systems, KAIST, Daejeon, Republic of Korea +1
Topology-induced Operators Reveal Complementary Graph Representations without Training
Sep 8, 2026Meng Qin, Jinqiang Cui, Hongwei Zheng +2Graph Representation Learning Graph Embedding
Department of Strategic & Advanced Interdisciplinary Research, Pengcheng Laboratory (PCL), Shenzhen, Guangdong, China. · Beijing Academy of Blockchain and Edge Computing, Beijing, China. · LMIB, NLSDE, and School of Artificial Intelligence, Beihang University, Beijing, China. +1
Measuring Memory and Generalization as Separable Geometric Channels: The Topo^2 Framework
Aug 31, 2026Zhanbo Zhang, Ming Liu, Qing WangNeural Network Generalization Neural Network Memorization
Anhui iFlytek Yinglian Technology Co., Ltd.
Topological Simplification in Predictive Coding Networks
Aug 3, 2026Adam Shaw, Jiayu Li, Michael Sperling +2Predictive Coding Topological Representation Learning
University of Southern California 3551 Trousdale Parkway, Los Angeles, CA 90089
Differentiable Lifting for Topological Neural Networks
Aug 2, 2026Jorge Luiz Franco, Gabriel Duarte, Alexander Nikitin +3Graph Structure Learning Graph Representation Learning
University of São Paulo, Instituto Curvelo · Federal Institute of Ceará · Aalto University +3
TopoFormer: Topology Meets Attention for Graph Learning
Jul 30, 2026Md Joshem Uddin, Astrit Tola, Cuneyt Gurcan Akcora +1Graph Representation Learning Graph Classification
Department of Mathematical Science The University of Texas at Dallas Richardson, TX 75080, USA · Department of Mathematics Florida State University Tallahassee, FL 32306, USA · AI Initiative University of Central Florida Orlando, FL 32816, USA
Multi-Scale Structural Features for Continual, Comprehensible Visual Recognition in a Developmental Learning Framework
Jul 28, 2026Zeki Doruk ErdenClass-Incremental Learning Incremental Learning
Sabanci University, Istanbul, Turkey
TopoGR: Revealing and Preserving Latent Structure of Semantic ID in Generative Recommendation
Jul 28, 2026Ziyu Zheng, Zhengshun Du, Yaming Yang +5Semantic ID Recommendation Recommender Systems
Xidian University, Xi’an, China · Alibaba Beijing, China · University of Science and Technology of China Hefei, China
Masked Topology Modeling for Self-Supervised Learning on Parametric CAD
Jul 22, 2026Heinrich Jiang, Jennifer JangGraph SSL Parametric CAD Modeling
StoryGold AI
SeeSE3: Emergence of 3D Space in Vision Features
Jul 15, 2026Caroline Chen, Sayna Ebrahimi, Fedor Kitashov +4Geometric Representation Learning Visual Odometry
Google DeepMind
PHINN-EEG: Topological Time-Series Analysis of Dream-State EEG -- Dynamic Betti Curves for Dream Content Classification and Topology-Conditioned Neural Signal Synthesis
Jul 10, 2026Ren Takahashi, Emre Yusuf, Jayabrata BhaduriEEG Decoding Persistent Homology
Mugen.Codes (DBA of CapaCloud Corp, Wyoming)
TopoAgent: An Agentic Framework for Automated Topology Learning in Medical Imaging
Jun 29, 2026Guangyu Meng, Pengfei Gu, Xueyang Li +3Medical Image Analysis Persistent Homology
Dept. of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA · Dept. of Computer Science, The University of Texas Rio Grande Valley, Edinburg, TX, USA
PolyFlow: Continuous Topology Embedding Flow Matching for Artist-style Mesh Generation
Jun 25, 2026Chunshi Wang, Haohan Weng, Junliang Ye +9Flow Matching 3D Mesh Generation
1ZJU · 2Tencent · 3THU +3
Topological Data Analysis for High-Dimensional Dynamic Process Monitoring
Jun 18, 2026Angan Mukherjee, Tyler A. Soderstrom, Michael J. Kurtz +1Process Supervision Topological Representation Learning
Department of Chemical & Biological Engineering, University of Wisconsin-Madison, 1415 Engineering Drive, Madison, WI 53706, USA · ExxonMobil Technology and Engineering, 22777 Springwoods Village Pkwy, Spring, TX 77389, USA
Analytic Torsion and Spectral Gap Capture Persistent-Laplacian Performance
Jun 15, 2026Jernej Grlj, Aaron D. LaudaDimensionality Reduction Spectral Methods
Department of Mathematics University of Southern California Los Angeles, CA 90089 · Department of Mathematics Department of Physics University of Southern California Los Angeles, CA 90089
Encoding the Euler Characteristic Transform
Jun 9, 2026Nello Blaser, Odin Hoff Gardaa, Lars M. Salbu +2Representation Learning Geometric Representation Learning
Department of Informatics, University of Bergen, Norway · Department of Informatics, University of Fribourg, Switzerland
Constructing VAE Latent Spaces with Prescribed Topology
Jun 5, 2026Jilles S. van Hulst, Jakub M. Tomczak, W. P. M. H. Heemels +1Variational Autoencoders Manifold Learning
Control Systems Technology Section, Department of Mechanical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands. · The research is carried out as part of the ITEA4 20216 ASIMOV project.
Learning Coherent Representations: A Topological Approach to Interpretability
Jun 1, 2026Sigurd Gaukstad, Melvin Vaupel, Valdemar Kargård Olsen +2Representation Learning Neural Representation Geometry
Department of Mathematical Sciences, NTNU, N-7491 Trondheim, Norway · Kavli Institute for Systems Neuroscience, NTNU, Trondheim, Norway
Beyond Instance-Level Self-Supervision in 3D Multi-Modal Medical Imaging
May 14, 2026Tan Pan, Shuhao Mei, Yixuan Sun +8Representation Learning Multimodal Robustness
Fudan University, China · Shanghai Academy of AI for Science, China · Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore +2
Beyond Point-wise Neural Collapse: A Topology-Aware Hierarchical Classifier for Class-Incremental Learning
May 12, 2026Huiyu Yi, Zhiming Xu, Dunwei Tu +3Class-Incremental Learning Prototype-Based Classification
National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China · School of Artificial Intelligence, Nanjing University, Nanjing, China · School of Computer Science, Nanjing University, Nanjing, China

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TIRA: Tumor Immune Representation Adaptation for Zero-Shot Cross-Cancer MSI and TMB Prediction

Dasari Naga Raju

Independent Researcher, Andhra Pradesh, India

Clinical Prediction Domain Generalization Vision Foundation Model Adaptation Topological Representation Learning

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Microsatellite instability-high (MSI-H) and high tumor mutational burden (TMB-H) are clinically relevant biomarkers, yet their histopathological prediction remains challenging when models are transferred across morphologically distinct cancer types. Immune-associated spatial patterns can persist across cancers despite these morphological differences, but foundation-model-based predictors trained on a single cancer do not explicitly use this information, limiting cross-cancer generalization. To address this limitation, we propose TIRA (Tumor Immune Representation Adaptation), a target-free framework that refines frozen foundation-model representations using spatial immune topology, without requiring target-domain data during model development or test-time adaptation. TIRA uses a topology-supervised biology representation to condition tile-level attention while pooling only morphological features for joint MSI and TMB prediction. We train TIRA on TCGA-COAD+READ and evaluate it zero-shot on CPTAC-COAD, TCGA-STAD, TCGA-UCEC, and CPTAC-UCEC, covering cross-site, cross-cancer, and combined cross-cancer-site distribution shifts under UNI2, CONCH, and Virchow2. With UNI2, TIRA improved zero-shot AUROC on TCGA-STAD from 0.633 to 0.766 for MSI and from 0.651 to 0.772 for TMB. Source-derived spatial immune topology improved the cross-cancer robustness of frozen pathology foundation-model representations.

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