Haitz Sáez de Ocáriz Borde

44 papers A* 6Journal 35Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Approximation Rates and VC-Dimension Bounds for (P)ReLU MLP Mixture of Experts. Trans. Mach. Learn. Res. Anastasis Kratsios, Haitz Sáez de Ocáriz Borde, Takashi Furuya, Marc T. Law
2025	J	`jnl`	Assessing the Geographic Generalization and Physical Consistency of Generative Models for Climate Downscaling. CoRR Carlo Saccardi, Maximilian Pierzyna, Haitz Sáez de Ocáriz Borde, Simone Monaco, Cristian Meo, Pietro Liò, Rudolf Saathof, Geethu Joseph, Justin Dauwels
2025	J	`jnl`	Beyond Parallelism: Synergistic Computational Graph Effects in Multi-Head Attention. CoRR Haitz Sáez de Ocáriz Borde
2025	J	`jnl`	Bridging Graph and State-Space Modeling for Intensive Care Unit Length of Stay Prediction. CoRR Shuqi Zi, Haitz Sáez de Ocáriz Borde, Emma Rocheteau, Pietro Lio'
2025	J	`jnl`	Closed-Form Diffusion Models. Trans. Mach. Learn. Res. Christopher Scarvelis, Haitz Sáez de Ocáriz Borde, Justin Solomon
2025	J	`jnl`	Fine-Tuning Next-Scale Visual Autoregressive Models with Group Relative Policy Optimization. CoRR Matteo Gallici, Haitz Sáez de Ocáriz Borde
2025	J	`jnl`	Keep It Light! Simplifying Image Clustering Via Text-Free Adapters. CoRR Yicen Li, Haitz Sáez de Ocáriz Borde, Anastasis Kratsios, Paul D. McNicholas
2025	J	`jnl`	LoRA Fine-Tuning Without GPUs: A CPU-Efficient Meta-Generation Framework for LLMs. CoRR Reza Arabpour, Haitz Sáez de Ocáriz Borde, Anastasis Kratsios
2025	J	`jnl`	Mathematical Foundations of Geometric Deep Learning. CoRR Haitz Sáez de Ocáriz Borde, Michael M. Bronstein
2025	J	`jnl`	Mitigating Model Drift in Developing Economies Using Synthetic Data and Outliers. CoRR Ilyas Varshavskiy, Bonu Boboeva, Shuhrat Khalilbekov, Azizjon Azimi, Sergey Shulgin, Akhlitdin Nizamitdinov, Haitz Sáez de Ocáriz Borde
2025	A*	`conf`	Neural Spacetimes for DAG Representation Learning. ICLR Haitz Sáez de Ocáriz Borde, Anastasis Kratsios, Marc T. Law, Xiaowen Dong, Michael M. Bronstein
2025	J	`jnl`	Sharp Generalization Bounds for Foundation Models with Asymmetric Randomized Low-Rank Adapters. CoRR Anastasis Kratsios, Tin Sum Cheng, Aurélien Lucchi, Haitz Sáez de Ocáriz Borde
2025	J	`jnl`	Structured Captions Improve Prompt Adherence in Text-to-Image Models (Re-LAION-Caption 19M). CoRR Nicholas Merchant, Haitz Sáez de Ocáriz Borde, Andrei Cristian Popescu, Carlos Garcia Jurado Suarez
2025	J	`jnl`	Towards Quantifying Long-Range Interactions in Graph Machine Learning: a Large Graph Dataset and a Measurement. CoRR Huidong Liang, Haitz Sáez de Ocáriz Borde, Baskaran Sripathmanathan, Michael M. Bronstein, Xiaowen Dong
2024	A*	`conf`	Asymmetry in Low-Rank Adapters of Foundation Models. ICML Jiacheng Zhu, Kristjan H. Greenewald, Kimia Nadjahi, Haitz Sáez de Ocáriz Borde, Rickard Brüel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Justin Solomon
2024	J	`jnl`	Asymmetry in Low-Rank Adapters of Foundation Models. CoRR Jiacheng Zhu, Kristjan H. Greenewald, Kimia Nadjahi, Haitz Sáez de Ocáriz Borde, Rickard Brüel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Justin Solomon
2024	J	`jnl`	Breaking the Curse of Dimensionality with Distributed Neural Computation. CoRR Haitz Sáez de Ocáriz Borde, Takashi Furuya, Anastasis Kratsios, Marc T. Law
2024	J	`jnl`	Capacity bounds for hyperbolic neural network representations of latent tree structures. Neural Networks Anastasis Kratsios, Ruiyang Hong, Haitz Sáez de Ocáriz Borde
2024	J	`jnl`	DreamUp3D: Object-Centric Generative Models for Single-View 3D Scene Understanding and Real-to-Sim Transfer. CoRR Yizhe Wu, Haitz Sáez de Ocáriz Borde, Jack Collins, Oiwi Parker Jones, Ingmar Posner
2024	J	`jnl`	DreamUp3D: Object-Centric Generative Models for Single-View 3D Scene Understanding and Real-to-Sim Transfer. IEEE Robotics Autom. Lett. Yizhe Wu, Haitz Sáez de Ocáriz Borde, Jack Collins, Oiwi Parker Jones, Ingmar Posner
2024	—	`conf`	Metric Learning for Clifford Group Equivariant Neural Networks. GRaM Riccardo Ali, Paulina Kulyte, Haitz Sáez de Ocáriz Borde, Pietro Lio
2024	J	`jnl`	Metric Learning for Clifford Group Equivariant Neural Networks. CoRR Riccardo Ali, Paulina Kulyte, Haitz Sáez de Ocáriz Borde, Pietro Liò
2024	A*	`conf`	Neural Snowflakes: Universal Latent Graph Inference via Trainable Latent Geometries. ICLR Haitz Sáez de Ocáriz Borde, Anastasis Kratsios
2024	J	`jnl`	Neural Spacetimes for DAG Representation Learning. CoRR Haitz Sáez de Ocáriz Borde, Anastasis Kratsios, Marc T. Law, Xiaowen Dong, Michael M. Bronstein
2024	J	`jnl`	Scalable Message Passing Neural Networks: No Need for Attention in Large Graph Representation Learning. CoRR Haitz Sáez de Ocáriz Borde, Artem Lukoianov, Anastasis Kratsios, Michael M. Bronstein, Xiaowen Dong
2024	A*	`conf`	Score Distillation via Reparametrized DDIM. NeurIPS Artem Lukoianov, Haitz Sáez de Ocáriz Borde, Kristjan H. Greenewald, Vitor Guizilini, Timur M. Bagautdinov, Vincent Sitzmann, Justin M. Solomon
2024	J	`jnl`	Score Distillation via Reparametrized DDIM. CoRR Artem Lukoianov, Haitz Sáez de Ocáriz Borde, Kristjan H. Greenewald, Vitor Campagnolo Guizilini, Timur M. Bagautdinov, Vincent Sitzmann, Justin Solomon
2023	J	`jnl`	AMES: A Differentiable Embedding Space Selection Framework for Latent Graph Inference. CoRR Yuan Lu, Haitz Sáez de Ocáriz Borde, Pietro Liò
2023	—	`conf`	AMES: A differentiable embedding space selection framework for latent graph inference. NeurReps Yuan Lu, Haitz Sáez de Ocáriz Borde, Pietro Liò
2023	J	`jnl`	Capacity Bounds for Hyperbolic Neural Network Representations of Latent Tree Structures. CoRR Anastasis Kratsios, Ruiyang Hong, Haitz Sáez de Ocáriz Borde
2023	J	`jnl`	Closed-Form Diffusion Models. CoRR Christopher Scarvelis, Haitz Sáez de Ocáriz Borde, Justin Solomon
2023	J	`jnl`	Gromov-Hausdorff Distances for Comparing Product Manifolds of Model Spaces. CoRR Haitz Sáez de Ocáriz Borde, Alvaro Arroyo, Ismael Morales, Ingmar Posner, Xiaowen Dong
2023	A*	`conf`	Latent Graph Inference using Product Manifolds. ICLR Haitz Sáez de Ocáriz Borde, Anees Kazi, Federico Barbero, Pietro Liò
2023	A*	`conf`	Neural Latent Geometry Search: Product Manifold Inference via Gromov-Hausdorff-Informed Bayesian Optimization. NeurIPS Haitz Sáez de Ocáriz Borde, Alvaro Arroyo, Ismael Morales, Ingmar Posner, Xiaowen Dong
2023	J	`jnl`	Neural Latent Geometry Search: Product Manifold Inference via Gromov-Hausdorff-Informed Bayesian Optimization. CoRR Haitz Sáez de Ocáriz Borde, Alvaro Arroyo, Ismael Morales, Ingmar Posner, Xiaowen Dong
2023	J	`jnl`	Neural Snowflakes: Universal Latent Graph Inference via Trainable Latent Geometries. CoRR Haitz Sáez de Ocáriz Borde, Anastasis Kratsios
2023	J	`jnl`	Projections of Model Spaces for Latent Graph Inference. CoRR Haitz Sáez de Ocáriz Borde, Alvaro Arroyo, Ingmar Posner
2022	J	`jnl`	Graph Neural Network Expressivity and Meta-Learning for Molecular Property Regression. CoRR Haitz Sáez de Ocáriz Borde, Federico Barbero
2022	J	`jnl`	Latent Graph Inference using Product Manifolds. CoRR Haitz Sáez de Ocáriz Borde, Anees Kazi, Federico Barbero, Pietro Liò
2022	—	`conf`	Sheaf Neural Networks with Connection Laplacians. TAG-ML Federico Barbero, Cristian Bodnar, Haitz Sáez de Ocáriz Borde, Michael M. Bronstein, Petar Velickovic, Pietro Liò
2022	J	`jnl`	Sheaf Neural Networks with Connection Laplacians. CoRR Federico Barbero, Cristian Bodnar, Haitz Sáez de Ocáriz Borde, Michael M. Bronstein, Petar Velickovic, Pietro Liò
2021	J	`jnl`	Interpretability in deep learning for finance: a case study for the Heston model. CoRR Damiano Brigo, Xiaoshan Huang, Andrea Pallavicini, Haitz Sáez de Ocáriz Borde
2021	J	`jnl`	Latent Space based Memory Replay for Continual Learning in Artificial Neural Networks. CoRR Haitz Sáez de Ocáriz Borde
2021	J	`jnl`	Multi-Task Learning based Convolutional Models with Curriculum Learning for the Anisotropic Reynolds Stress Tensor in Turbulent Duct Flow. CoRR Haitz Sáez de Ocáriz Borde, David Sondak, Pavlos Protopapas