


default search action
2nd NeurReps 2023: New Orleans, Lousiana, USA
- Sophia Sanborn, Christian Shewmake, Simone Azeglio, Nina Miolane:

NeurIPS Workshop on Symmetry and Geometry in Neural Representations, 16 December 2023, New Orleans, Lousiana, USA. Proceedings of Machine Learning Research 228, PMLR 2023 - Sophia Sanborn, Christian Shewmake, Simone Azeglio, Nina Miolane:

Preface. i-vii - Yu He, Cristian Bodnar, Pietro Liò:

Sheaf-based Positional Encodings for Graph Neural Networks. 1-18 - Yuan Lu, Haitz Sáez de Ocáriz Borde, Pietro Liò:

AMES: A differentiable embedding space selection framework for latent graph inference. 19-34 - Duc Thien Nguyen, Manh Duc Tuan Nguyen, Truong Son Hy, Risi Kondor:

Fast Temporal Wavelet Graph Neural Networks. 35-54 - Cody Tipton, Elizabeth Coda, Davis Brown, Alyson Bittner, Jung Lee, Grayson Jorgenson, Tegan Emerson, Henry Kvinge:

Haldane bundles: a dataset for learning to predict the Chern number of line bundles on the torus. 55-74 - Henry Kvinge, Grayson Jorgenson, Davis Brown, Charles Godfrey, Tegan Emerson:

Internal representations of vision models through the lens of frames on data manifolds. 75-115 - Moein Khajehnejad, Forough Habibollahi, Alon Loeffler, Brett J. Kagan, Adeel Razi:

On complex network dynamics of an in vitro neuronal system during Rest and Gameplay. 116-128 - Sho Sonoda, Hideyuki Ishi, Isao Ishikawa, Masahiro Ikeda:

Joint Group Invariant Functions on Data-Parameter Domain Induce Universal Neural Networks. 129-144 - Chuqin Geng, Xiaojie Xu, Haolin Ye, Xujie Si:

Scalar Invariant Networks with Zero Bias. 145-163 - Rubén Ballester, Carles Casacuberta, Sergio Escalera:

Decorrelating neurons using persistence. 164-182 - Marco Pegoraro, Riccardo Marin, Arianna Rampini, Simone Melzi, Luca Cosmo, Emanuele Rodolà:

Spectral Maps for Learning on Subgraphs. 183-205 - Antonio Briola, Yuanrong Wang, Silvia Bartolucci, Tomaso Aste:

Homological Convolutional Neural Networks. 206-231 - Xinran Han, Todd E. Zickler:

Curvature Fields from Shading Fields. 232-254 - Christopher Versteeg, Andrew R. Sedler, Jonathan D. McCart, Chethan Pandarinath:

Expressive dynamics models with nonlinear injective readouts enable reliable recovery of latent features from neural activity. 255-278 - Suryaka Suresh, Vinayak Abrol, Anshul Thakur:

Pitfalls in Measuring Neural Transferability. 279-291 - Philip Andrew Mansfield, Arash Afkanpour, Warren Richard Morningstar, Karan Singhal:

Random field augmentations for self-supervised representation learning. 292-302 - Colin Kohler, Nathan Vaska, Ramya Muthukrishnan, Whangbong Choi, Jung Yeon Park, Justin Goodwin, Rajmonda Caceres, Robin Walters:

Symmetric models for radar response modeling. 303-323 - Thomas Walker, Octave Mariotti, Amir Vaxman, Hakan Bilen:

Explicit neural surfaces: learning continuous geometry with deformation fields. 324-345 - Jiaang Li, Antonia Karamolegkou, Yova Kementchedjhieva, Mostafa Abdou, Anders Søgaard:

Structural Similarities Between Language Models and Neural Response Measurements. 346-365 - Aditya Chetan, Nipun Kwatra:

Distance Learner: Incorporating Manifold Prior to Model Training. 366-387 - Donato Crisostomi, Irene Cannistraci, Luca Moschella, Pietro Barbiero, Marco Ciccone, Pietro Liò, Emanuele Rodolà:

From charts to atlas: Merging latent spaces into one. 388-404 - James Mochizuki-Freeman, Md Rysul Kabir, Mitesh Gulecha, Zoran Tiganj:

Geometry of abstract learned knowledge in deep RL agents. 405-424 - John J. Vastola:

Optimal packing of attractor states in neural representations. 425-442 - Arif Dönmez:

Discovering latent causes and memory modification: A computational approach using symmetry and geometry. 443-458

manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.


Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCID














