:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	de Souza, Daniel Augusto, Zhu, Yuchen, Cunningham, Harry Jake, Saporito, Yuri, Mesquita, Diego, Deisenroth, Marc Peter
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2510.16675
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Reparameterized Multi-Resolution Convolutions for Long Sequence Modelling
by: Cunningham, Harry Jake, et al.
Published: (2024)

Nonparametric Instrumental Variable Regression through Stochastic Approximate Gradients
by: Fonseca, Yuri, et al.
Published: (2024)

Random Gradient-Free Optimization in Infinite Dimensional Spaces
by: Peixoto, Caio Lins, et al.
Published: (2025)

Gaussian Processes on Cellular Complexes
by: Alain, Mathieu, et al.
Published: (2023)

Learning Physical Operators using Neural Operators
by: Gopakumar, Vignesh, et al.
Published: (2026)

Probabilistic Weather Forecasting with Hierarchical Graph Neural Networks
by: Oskarsson, Joel, et al.
Published: (2024)

Streaming Bayes GFlowNets
by: da Silva, Tiago, et al.
Published: (2024)

Matérn Gaussian Processes on Graphs
by: Borovitskiy, Viacheslav, et al.
Published: (2020)

Iterated INLA for State and Parameter Estimation in Nonlinear Dynamical Systems
by: Anderka, Rafael, et al.
Published: (2024)

RDM: Recurrent Diffusion Model for Human Motion Generation
by: Mohamed, Mirgahney, et al.
Published: (2024)

Scalable Data Assimilation with Message Passing
by: Key, Oscar, et al.
Published: (2024)

Plasma Surrogate Modelling using Fourier Neural Operators
by: Gopakumar, Vignesh, et al.
Published: (2023)

IKNO: Infinite-order Kernel Neural Operators
by: Zhu, Pengyuan, et al.
Published: (2026)

Gaussian Sheaf Neural Networks
by: Ribeiro, André, et al.
Published: (2026)

A Unifying Variational Framework for Gaussian Process Motion Planning
by: Cosier, Lucas, et al.
Published: (2023)

In-n-Out: Calibrating Graph Neural Networks for Link Prediction
by: Nascimento, Erik, et al.
Published: (2024)

Valid Error Bars for Neural Weather Models using Conformal Prediction
by: Gopakumar, Vignesh, et al.
Published: (2024)

Reverse-BSDE Monte Carlo
by: Batista, Jairon H. N., et al.
Published: (2025)

Boosted GFlowNets: Improving Exploration via Sequential Learning
by: Dall'Antonia, Pedro, et al.
Published: (2025)

Cooperative Sheaf Neural Networks
by: Ribeiro, André, et al.
Published: (2025)

Differentially Private E-Values
by: Csillag, Daniel, et al.
Published: (2025)

Parameter Efficient Fine-tuning via Explained Variance Adaptation
by: Paischer, Fabian, et al.
Published: (2024)

Deep Learning and Elicitability for McKean-Vlasov FBSDEs With Common Noise
by: Antunes, Felipe J. P., et al.
Published: (2025)

RotRNN: Modelling Long Sequences with Rotations
by: Biegun, Kai, et al.
Published: (2024)

Variational Nearest Neighbor Gaussian Process
by: Wu, Luhuan, et al.
Published: (2022)

Calibrated Physics-Informed Uncertainty Quantification
by: Gopakumar, Vignesh, et al.
Published: (2025)

Embarrassingly Parallel GFlowNets
by: da Silva, Tiago, et al.
Published: (2024)

Distill n' Explain: explaining graph neural networks using simple surrogates
by: Pereira, Tamara, et al.
Published: (2023)

Quantum neural networks form Gaussian processes
by: García-Martín, Diego, et al.
Published: (2023)

A Gap Between the Gaussian RKHS and Neural Networks: An Infinite-Center Asymptotic Analysis
by: Kumar, Akash, et al.
Published: (2025)

When Can Proxies Improve the Sample Complexity of Preference Learning?
by: Zhu, Yuchen, et al.
Published: (2024)

Online Infinite-Dimensional Regression: Learning Linear Operators
by: Raman, Vinod, et al.
Published: (2023)

RHYME-XT: A Neural Operator for Spatiotemporal Control Systems
by: Ruiter, Marijn, et al.
Published: (2026)

Infinite-dimensional Diffusion Bridge Simulation via Operator Learning
by: Yang, Gefan, et al.
Published: (2024)

Avoid What You Know: Divergent Trajectory Balance for GFlowNets
by: Dall'Antonia, Pedro, et al.
Published: (2026)

Geometric Laplace Neural Operator
by: Tang, Hao, et al.
Published: (2025)

Gaussian Plane-Wave Neural Operator for Electron Density Estimation
by: Kim, Seongsu, et al.
Published: (2024)

Provable and scalable quantum Gaussian processes for quantum learning
by: Jäger, Jonas, et al.
Published: (2026)

Neural-POD: A Plug-and-Play Neural Operator Framework for Infinite-Dimensional Functional Nonlinear Proper Orthogonal Decomposition
by: Mou, Changhong, et al.
Published: (2026)

Flexible Infinite-Width Graph Convolutional Neural Networks
by: Anson, Ben, et al.
Published: (2024)