Get started
Author

Haitz Sáez de Ocáriz Borde

Observed names: Borde, Haitz Saez de Ocariz, Borde, Haitz Sáez de Ocáriz, Haitz De Ocáriz Borde, Haitz Saéz de Ocáriz Borde, Haitz Sáez de Ocáriz Borde, Haitz Sáez De Ocáriz Borde, de Ocariz Borde H. S.
ORCID: 0009-0000-2297-7750
Observed ORCID: 0009-0000-2297-7750
OpenAlex ID: A5022524322
Convolutional neural network models and interpretability for the anisotropic reynolds stress tensor in turbulent one-dimensional flows
2021 · Haitz Sáez de Ocáriz Borde, David Sondak, et al. · Journal of Turbulence · 14
Interpretability in deep learning for finance: A case study for the Heston model
2025 · Damiano Brigo, Xiaoshan Huang, et al. · Risk sciences. · 11
Score Distillation via Reparametrized DDIM
2024 · Artem Lukoianov, Haitz De Ocáriz Borde, et al. · neural information processing systems · 6
PDF
DreamUp3D: Object-Centric Generative Models for Single-View 3D Scene Understanding and Real-to-Sim Transfer
2024 · Yizhe Wu, Haitz Sáez de Ocáriz Borde, et al. · IEEE Robotics and Automation Letters · 4
PDF
Asymmetry in Low-Rank Adapters of Foundation Models
2024 · Zhu, Jiacheng, Greenewald, Kristjan, et al. · arXiv (Cornell University) · 3
PDF
Projections of Model Spaces for Latent Graph Inference
2023 · Borde, Haitz Sáez de Ocáriz, Arroyo, Álvaro, et al. · arXiv (Cornell University) · 3
PDF
Neural Spacetimes for DAG Representation Learning
2024 · Borde, Haitz Sáez de Ocáriz, Kratsios, Anastasis, et al. · arXiv (Cornell University) · 2
PDF
Neural Snowflakes: Universal Latent Graph Inference via Trainable Latent Geometries
2023 · Borde, Haitz Sáez de Ocáriz, Kratsios, Anastasis · arXiv (Cornell University) · 2
PDF
Latent Graph Inference using Product Manifolds
2022 · Borde, Haitz Sáez de Ocáriz, Kazi, Anees, et al. · arXiv (Cornell University) · 2
PDF
Graph Neural Network Expressivity and Meta-Learning for Molecular Property Regression
2022 · Borde, Haitz Sáez de Ocáriz, Barbero, Federico · arXiv (Cornell University) · 2
PDF
Capacity bounds for hyperbolic neural network representations of latent tree structures
2024 · Anastasis Kratsios, Ruiyang Hong, et al. · Neural Networks · 1
PDF
AMES: A Differentiable Embedding Space Selection Framework for Latent Graph Inference
2023 · Lu, Yuan, Borde, Haitz Sáez de Ocáriz, et al. · arXiv (Cornell University) · 1
PDF
Neural Latent Geometry Search: Product Manifold Inference via Gromov-Hausdorff-Informed Bayesian Optimization
2023 · Borde, Haitz Saez de Ocariz, Arroyo, Alvaro, et al. · arXiv (Cornell University) · 1
PDF
Neural Latent Geometry Search: Product Manifold Inference via Gromov-Hausdorff-Informed Bayesian Optimization
2023 · Haitz Sáez De Ocáriz Borde, Alvaro Arroyo, et al. · neural information processing systems · 1
Multi-Task Learning based Convolutional Models with Curriculum Learning for the Anisotropic Reynolds Stress Tensor in Turbulent Duct Flow
2021 · Borde, Haitz Sáez de Ocáriz, Sondak, David, et al. · arXiv (Cornell University) · 1
PDF
Stop guessing thinning distances: a data-driven framework for spatial thinning parametrization for ecological modelling
2026 · Héctor Ibáñez, Gorka Bidegain, et al. · bioRxiv (Cold Spring Harbor Laboratory)
PDF
Airfoil2Vec: Spectral Geometry-Conditioned Neural Surrogate Models for Airfoil Aerodynamics and a Downforce-Generating CFD Dataset
2026 · Borde, Haitz Sáez de Ocáriz, Savarino, Flavio, et al. · arXiv (Cornell University)
PDF
Evaluating Open-Weight E-Commerce Agents with Environment-Grounded Verification
2026 · Shah, Nimit, Borde, Haitz Sáez de Ocáriz · arXiv (Cornell University)
PDF
Answer-Distribution Trajectories: A Stochastic-Dynamics View of LLM Reasoning
2026 · Català, Mar Gonzàlez I, Borde, Haitz Sáez de Ocáriz, et al. · arXiv (Cornell University)
PDF
Looped Language Models Improve Compositional Tool Calling
2026 · Popescu, Andrei Cristian, Borde, Haitz Sáez de Ocáriz, et al. · arXiv (Cornell University)
PDF
Adaptive Depth in Looped Transformers: Diagnosing Learned Halting Gates and Trajectory Readouts
2026 · Popescu, Andrei Cristian, Borde, Haitz Sáez de Ocáriz, et al. · arXiv (Cornell University)
PDF
Algorithmic Foundations of Deep Learning: Complexity-Theoretic Rates and a Characterization of Universal Approximation
2026 · Kratsios, Anastasis, Brugiapaglia, Simone, et al. · arXiv (Cornell University)
PDF
Classification Fields: Arbitrarily Fine Recursive Hierarchical Clustering From Few Examples
2026 · Li, Yicen, Hong, Ruiyang, et al. · arXiv (Cornell University)
PDF
Every Feedforward Neural Network Definable in an o-Minimal Structure Has Finite Sample Complexity
2026 · Kratsios, Anastasis, Cousins, Gregory, et al. · arXiv (Cornell University)
PDF
Soro: A Lightweight Foundation Model and Chatbot for Tajik
2026 · Liashkov, Stanislav, Borde, Haitz Sáez de Ocáriz, et al. · arXiv (Cornell University)
PDF
Works count: 51
Citation count: 61
H-index: 4
I10-index: 2
Year
Topic
Type