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ORCIDTAG-ML 2022, Virtual
- Alexander Cloninger, Timothy Doster, Tegan Emerson, Manohar Kaul, Ira Ktena, Henry Kvinge, Nina Miolane, Bastian Rice, Sarah Tymochko, Guy Wolf:
Topological, Algebraic and Geometric Learning Workshops 2022, 25-22 July 2022, Virtual. Proceedings of Machine Learning Research 196, PMLR 2022 - Alexander Cloninger, Timothy Doster, Tegan Emerson, Manohar Kaul, Ira Ktena, Henry Kvinge, Nina Miolane, Bastian Rice, Sarah Tymochko, Guy Wolf:
Preface. 1-5 - Aishwarya H. Balwani, Jakob Krzyston:
Zeroth-Order Topological Insights into Iterative Magnitude Pruning. 6-16 - Jacob Bamberger:
A Topological characterisation of Weisfeiler-Leman equivalence classes. 17-27 - Federico Barbero, Cristian Bodnar, Haitz Sáez de Ocáriz Borde, Michael M. Bronstein, Petar Velickovic, Pietro Liò:
Sheaf Neural Networks with Connection Laplacians. 28-36 - Ido Ben-Shaul, Shai Dekel:
Nearest Class-Center Simplification through Intermediate Layers. 37-47 - Yuzhao Chen, Yatao Bian, Jiying Zhang, Xi Xiao, Tingyang Xu, Yu Rong:
Diversified Multiscale Graph Learning with Graph Self-Correction. 48-54 - Nutan Chen, Patrick van der Smagt, Botond Cseke:
Local Distance Preserving Auto-encoders using Continuous kNN Graphs. 55-66 - Joyce A. Chew, Holly R. Steach, Siddharth Viswanath, Hau-Tieng Wu, Matthew J. Hirn, Deanna Needell, Matthew D. Vesely, Smita Krishnaswamy, Michael Perlmutter:
The Manifold Scattering Transform for High-Dimensional Point Cloud Data. 67-78 - Elizabeth Coda, Nico Courts, Colby Wight, Loc Truong, WoongJo Choi, Charles Godfrey, Tegan Emerson, Keerti Kappagantula, Henry Kvinge:
Fiber Bundle Morphisms as a Framework for Modeling Many-to-Many Maps. 79-85 - Debajyoti Datta, Shashwat Kumar, Laura E. Barnes, P. Thomas Fletcher:
A Geometrical Approach to Finding Difficult Examples in Language. 86-95 - Thibault de Surrel, Felix Hensel, Mathieu Carrière, Théo Lacombe, Yuichi Ike, Hiroaki Kurihara, Marc Glisse, Frédéric Chazal:
RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds. 96-106 - Ben Finkelshtein, Chaim Baskin, Haggai Maron, Nadav Dym:
A Simple and Universal Rotation Equivariant Point-Cloud Network. 107-115 - Stephen Fitz:
The Shape of Words - topological structure in natural language data. 116-123 - Thomas Gebhart:
Graph Convolutional Networks from the Perspective of Sheaves and the Neural Tangent Kernel. 124-132 - Rita González-Márquez, Philipp Berens, Dmitry Kobak:
Two-dimensional visualization of large document libraries using t-SNE. 133-141 - Celia Hacker, Bastian Rieck:
On the Surprising Behaviour of \textttnode2vec. 142-151 - Keaton Hamm, Mohamed Meskini, HanQin Cai:
Riemannian CUR Decompositions for Robust Principal Component Analysis. 152-160 - Chester Holtz, Gal Mishne, Alexander Cloninger:
Evaluating Disentanglement in Generative Models Without Knowledge of Latent Factors. 161-171 - Truong Son Hy, Risi Kondor:
Multiresolution Matrix Factorization and Wavelet Networks on Graphs. 172-182 - Grayson Jorgenson, Henry Kvinge, Tegan Emerson, Colin C. Olson:
Random Filters for Enriching the Discriminatory power of Topological Representations. 183-188 - Kai Yi, Jialin Chen, Yu Guang Wang, Bingxin Zhou, Pietro Liò, Yanan Fan, Jan Hamann:
APPROXIMATE EQUIVARIANCE SO(3) NEEDLET CONVOLUTION. 189-198 - Lara Kassab, Scott Howland, Henry Kvinge, Keerti Sahithi Kappagantula, Tegan Emerson:
TopTemp: Parsing Precipitate Structure from Temper Topology. 199-205 - Ekaterina Khramtsova, Guido Zuccon, Xi Wang, Mahsa Baktashmotlagh:
Rethinking Persistent Homology For Visual Recognition. 206-215 - Shiying Li, Abu Hasnat Mohammad Rubaiyat, Gustavo K. Rohde:
Geodesic Properties of a Generalized Wasserstein Embedding for Time Series Aanalysis. 216-225 - Mario Lino, Stathi Fotiadis, Anil A. Bharath, Chris D. Cantwell:
REMuS-GNN: A Rotation-Equivariant Model for Simulating Continuum Dynamics. 226-236 - Xiang Liu, Kelin Xia:
Persistent tor-algebra based stacking ensemble learning (PTA-SEL) for protein-protein binding affinity prediction. 237-247 - Zhiwei Liu, Lin Meng, Fei Jiang, Jiawei Zhang, Philip S. Yu:
Deoscillated Adaptive Graph Collaborative Filtering. 248-257 - Johannes F. Lutzeyer, Changmin Wu, Michalis Vazirgiannis:
Sparsifying the Update Step in Graph Neural Networks. 258-268 - Adele Myers, Saiteja Utpala, Shubham Talbar, Sophia Sanborn, Christian Shewmake, Claire Donnat, Johan Mathe, Rishi Sonthalia, Xinyue Cui, Tom Szwagier, Arthur Pignet, Andri Bergsson, Søren Hauberg, Dmitriy Nielsen, Stefan Sommer, David A. Klindt, Erik Hermansen, Melvin Vaupel, Benjamin A. Dunn, Jeffrey Xiong, Noga Aharony, Itsik Pe'er, Felix Ambellan, Martin Hanik, Esfandiar Nava-Yazdani, Christoph von Tycowicz, Nina Miolane:
ICLR 2022 Challenge for Computational Geometry & Topology: Design and Results. 269-276 - Navya Nagananda, Breton L. Minnehan, Andreas E. Savakis:
Robust $L_p$-Norm Linear Discriminant Analysis with Proxy Matrix Optimization. 277-286 - Sun Woo Park, Yun Young Choi, Dosang Joe, U Jin Choi, Youngho Woo:
The PWLR graph Representation: A Persistent Weisfeiler-Lehman Scheme with Random Walks for Graph Classification. 287-297 - Rishi Sonthalia, Anna C. Gilbert, Matthew Durham:
CubeRep: Learning Relations Between Different Views of Data. 298-303 - Elise van der Pol, Ian Gemp, Yoram Bachrach:
Stochastic Parallelizable Eigengap Dilation for Large Graph Clustering. 304-311 - Daniel J. Williams, Song Liu:
Score Matching for Truncated Density Estimation on a Manifold. 312-321 - Peter Xenopoulos, Gromit Chan, Harish Doraiswamy, Luis Gustavo Nonato, Brian Barr, Cláudio T. Silva:
GALE: Globally Assessing Local Explanations. 322-331 - Léon Migus, Yuan Yin, Jocelyn Ahmed Mazari, Patrick Gallinari:
Multi-Scale Physical Representations for Approximating PDE Solutions with Graph Neural Operators. 332-340
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