:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Krahn, Maximilian, Garg, Vikas
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning
Accès en ligne:	https://arxiv.org/abs/2507.12380
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Topological Neural Networks go Persistent, Equivariant, and Continuous
par: Verma, Yogesh, et autres
Publié: (2024)

Let Physics Guide Your Protein Flows: Topology-aware Unfolding and Generation
par: Verma, Yogesh, et autres
Publié: (2025)

The Logical Expressiveness of Topological Neural Networks
par: Akbari, Amirreza, et autres
Publié: (2026)

Margin-calibrated Classifier Guidance for Property-driven Synthesis Planning
par: Laabid, Najwa, et autres
Publié: (2026)

Devil is in the Details: Density Guidance for Detail-Aware Generation with Flow Models
par: Karczewski, Rafał, et autres
Publié: (2025)

Heterophily-informed Message Passing
par: Wang, Haishan, et autres
Publié: (2025)

Robust Simulation-Based Inference under Missing Data via Neural Processes
par: Verma, Yogesh, et autres
Publié: (2025)

Contraction and Hourglass Persistence for Learning on Graphs, Simplices, and Cells
par: Ji, Mattie, et autres
Publié: (2026)

Heat and Matérn Kernels on Matchings
par: Eremeev, Dmitry, et autres
Publié: (2026)

Diffusion Twigs with Loop Guidance for Conditional Graph Generation
par: Mercatali, Giangiacomo, et autres
Publié: (2024)

Network Interdiction Goes Neural
par: Zhang, Lei, et autres
Publié: (2024)

On topological descriptors for graph products
par: Ji, Mattie, et autres
Publié: (2025)

Graph Persistence goes Spectral
par: Ji, Mattie, et autres
Publié: (2025)

Algebraic Positional Encodings
par: Kogkalidis, Konstantinos, et autres
Publié: (2023)

Diffusion Models as Cartoonists: The Curious Case of High Density Regions
par: Karczewski, Rafał, et autres
Publié: (2024)

Employing Federated Learning for Training Autonomous HVAC Systems
par: Hagström, Fredrik, et autres
Publié: (2024)

Kernel-Adaptive PI-ELMs for Forward and Inverse Problems in PDEs with Sharp Gradients
par: Dwivedi, Vikas, et autres
Publié: (2025)

What Ails Generative Structure-based Drug Design: Expressivity is Too Little or Too Much?
par: Karczewski, Rafał, et autres
Publié: (2024)

Quantum Generator Kernels
par: Altmann, Philipp, et autres
Publié: (2026)

ClimODE: Climate and Weather Forecasting with Physics-informed Neural ODEs
par: Verma, Yogesh, et autres
Publié: (2024)

The Spacetime of Diffusion Models: An Information Geometry Perspective
par: Karczewski, Rafał, et autres
Publié: (2025)

Canonicalizing Multimodal Contrastive Representation Learning
par: Gupta, Sharut, et autres
Publié: (2026)

Projected Stochastic Gradient Descent with Quantum Annealed Binary Gradients
par: Krahn, Maximilian, et autres
Publié: (2023)

Faster Low-Rank Approximation and Kernel Ridge Regression via the Block-Nyström Method
par: Garg, Sachin, et autres
Publié: (2025)

TADPO: Reinforcement Learning Goes Off-road
par: Wu, Zhouchonghao, et autres
Publié: (2026)

The GeometricKernels Package: Heat and Matérn Kernels for Geometric Learning on Manifolds, Meshes, and Graphs
par: Mostowsky, Peter, et autres
Publié: (2024)

Positional Encoding meets Persistent Homology on Graphs
par: Verma, Yogesh, et autres
Publié: (2025)

Fast, Accurate and Interpretable Graph Classification with Topological Kernels
par: Wesołowski, Adam, et autres
Publié: (2025)

Equivariant Denoisers Cannot Copy Graphs: Align Your Graph Diffusion Models
par: Laabid, Najwa, et autres
Publié: (2024)

Explaining Kernel Clustering via Decision Trees
par: Fleissner, Maximilian, et autres
Publié: (2024)

Omnipresent Yet Overlooked: Heat Kernels in Combinatorial Bayesian Optimization
par: Doumont, Colin, et autres
Publié: (2025)

Topological Neural Tangent Kernel
par: Krishnagopal, Sanjukta
Publié: (2026)

The Tsetlin Machine Goes Deep: Logical Learning and Reasoning With Graphs
par: Granmo, Ole-Christoffer, et autres
Publié: (2025)

The Map Equation Goes Neural: Mapping Network Flows with Graph Neural Networks
par: Blöcker, Christopher, et autres
Publié: (2023)

DNN-Based Topology Optimisation: Spatial Invariance and Neural Tangent Kernel
par: Dupuis, Benjamin, et autres
Publié: (2021)

Matérn Kernels for Tunable Implicit Surface Reconstruction
par: Weiherer, Maximilian, et autres
Publié: (2024)

Sketching the Heat Kernel: Using Gaussian Processes to Embed Data
par: Gilbert, Anna C., et autres
Publié: (2024)

Beyond Attention: Learning Spatio-Temporal Dynamics with Emergent Interpretable Topologies
par: Alisetti, Sai Vamsi, et autres
Publié: (2025)

Graph4GUI: Graph Neural Networks for Representing Graphical User Interfaces
par: Jiang, Yue, et autres
Publié: (2024)

A Little Human Data Goes A Long Way
par: Ashok, Dhananjay, et autres
Publié: (2024)