v1v2 (latest)

Neural Spacetimes for DAG Representation Learning

International Conference on Learning Representations (ICLR), 2024

25 August 2024

Haitz Sáez de Ocáriz Borde

Michael Bronstein

Papers citing "Neural Spacetimes for DAG Representation Learning"

29 / 29 papers shown

Title
Bridging Graph and State-Space Modeling for Intensive Care Unit Length of Stay Prediction Shuqi Zi Haitz Sáez de Ocáriz Borde Emma Rocheteau Pietro Lio Mamba 207 0 0 24 Aug 2025
Enhancing LLMs' Reasoning-Intensive Multimedia Search Capabilities through Fine-Tuning and Reinforcement Learning Jinzheng Li Sibo Ju Yanzhou Su Hongguang Li Yiqing Shen LRM 128 2 0 24 May 2025
Mixed-Curvature Decision Trees and Random Forests Philippe Chlenski Quentin Chu I. Pe’er 165 2 0 07 Jun 2024
Graph Metanetworks for Processing Diverse Neural Architectures Derek Lim Haggai Maron Marc T. Law Jonathan Lorraine James Lucas AI4CE 303 43 0 07 Dec 2023
AMES: A Differentiable Embedding Space Selection Framework for Latent Graph Inference Yuan Lu Haitz Sáez de Ocáriz Borde Pietro Lio 177 3 0 20 Nov 2023
Neural Snowflakes: Universal Latent Graph Inference via Trainable Latent GeometriesInternational Conference on Learning Representations (ICLR), 2023 Haitz Sáez de Ocáriz Borde Anastasis Kratsios 434 6 0 23 Oct 2023
Neural Latent Geometry Search: Product Manifold Inference via Gromov-Hausdorff-Informed Bayesian OptimizationNeural Information Processing Systems (NeurIPS), 2023 Haitz Sáez de Ocáriz Borde Alvaro Arroyo Ismael Morales Ingmar Posner Xiaowen Dong 334 12 0 09 Sep 2023
Capacity Bounds for Hyperbolic Neural Network Representations of Latent Tree StructuresNeural Networks (Neural Netw.), 2023 Anastasis Kratsios Rui Hong Haitz Sáez de Ocáriz Borde 206 5 0 18 Aug 2023
Optimal transport and Wasserstein distances for causal modelsBernoulli (Bernoulli), 2023 Patrick Cheridito Stephan Eckstein OT 230 14 0 24 Mar 2023
Out-of-distributional risk bounds for neural operators with applications to the Helmholtz equationJournal of Computational Physics (JCP), 2023 Jose Antonio Lara Benitez Takashi Furuya F. Faucher Anastasis Kratsios X. Tricoche Maarten V. de Hoop 303 32 0 27 Jan 2023
Latent Graph Inference using Product ManifoldsInternational Conference on Learning Representations (ICLR), 2022 Haitz Sáez de Ocáriz Borde Anees Kazi Federico Barbero Pietro Lio BDL 233 22 0 26 Nov 2022
Instance-Dependent Generalization Bounds via Optimal TransportJournal of machine learning research (JMLR), 2022 Songyan Hou Parnian Kassraie Anastasis Kratsios Andreas Krause Jonas Rothfuss 431 11 0 02 Nov 2022
Small Transformers Compute Universal Metric EmbeddingsJournal of machine learning research (JMLR), 2022 Anastasis Kratsios Valentin Debarnot Ivan Dokmanić 266 14 0 14 Sep 2022
Integral Probability Metrics PAC-Bayes BoundsNeural Information Processing Systems (NeurIPS), 2022 Ron Amit Baruch Epstein Shay Moran Ron Meir 382 22 0 01 Jul 2022
Bayesian Structure Learning with Generative Flow NetworksConference on Uncertainty in Artificial Intelligence (UAI), 2022 T. Deleu António Góis Chris C. Emezue M. Rankawat Damien Scieur Stefan Bauer Yoshua Bengio BDL 247 181 0 28 Feb 2022
Heterogeneous manifolds for curvature-aware graph embedding Francesco Di Giovanni Giulia Luise M. Bronstein 195 26 0 02 Feb 2022
Designing Universal Causal Deep Learning Models: The Geometric (Hyper)TransformerMathematical Finance (Math. Finance), 2022 Beatrice Acciaio Anastasis Kratsios G. Pammer OOD 361 28 0 31 Jan 2022
Directed Graph Embeddings in Pseudo-Riemannian Manifolds Aaron Sim Maciej Wiatrak Angus Brayne Páidí Creed Saee Paliwal 149 17 0 16 Jun 2021
Graph Neural Networks with Heterophily Jiong Zhu Ryan A. Rossi Anup B. Rao Tung Mai Nedim Lipka Nesreen Ahmed Danai Koutra 222 362 0 28 Sep 2020
Ultrahyperbolic Representation Learning M. Law J. Stam 399 27 0 01 Jul 2020
COT-GAN: Generating Sequential Data via Causal Optimal Transport Tianlin Xu L. Wenliang Michael Munn Beatrice Acciaio GAN CML 155 121 0 15 Jun 2020
Tree! I am no Tree! I am a Low Dimensional Hyperbolic Embedding Rishi Sonthalia A. Gilbert 236 57 0 08 May 2020
Open Graph Benchmark: Datasets for Machine Learning on GraphsNeural Information Processing Systems (NeurIPS), 2020 Weihua Hu Matthias Fey Marinka Zitnik Yuxiao Dong Hongyu Ren Bowen Liu Michele Catasta J. Leskovec 692 3,166 0 02 May 2020
Multi-scale Attributed Node Embedding Benedek Rozemberczki Carl Allen Rik Sarkar GNN 638 986 0 28 Sep 2019
Hyperbolic Neural Networks O. Ganea Gary Bécigneul Thomas Hofmann 219 704 0 23 May 2018
DAGs with NO TEARS: Continuous Optimization for Structure Learning Xun Zheng Bryon Aragam Pradeep Ravikumar Eric Xing NoLa CML OffRL 328 1,129 0 04 Mar 2018
Graph Attention NetworksInternational Conference on Learning Representations (ICLR), 2017 Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Lio Yoshua Bengio GNN 1.9K 23,539 0 30 Oct 2017
Semi-Supervised Classification with Graph Convolutional Networks Thomas Kipf Max Welling GNN SSL 1.7K 32,393 0 09 Sep 2016
Convolutional Neural Networks on Graphs with Fast Localized Spectral FilteringNeural Information Processing Systems (NeurIPS), 2016 M. Defferrard Xavier Bresson P. Vandergheynst GNN 801 8,175 0 30 Jun 2016