:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Antipov, Egor, Palma, Alessandro, Consoli, Lorenzo, Günnemann, Stephan, Dittadi, Andrea, Theis, Fabian J.
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2602.24201
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Modeling Microenvironment Trajectories on Spatial Transcriptomics with NicheFlow
by: Sakalyan, Kristiyan, et al.
Published: (2025)

Enforcing Latent Euclidean Geometry in Single-Cell VAEs for Manifold Interpolation
by: Palma, Alessandro, et al.
Published: (2025)

Multi-Modal and Multi-Attribute Generation of Single Cells with CFGen
by: Palma, Alessandro, et al.
Published: (2024)

GENOT: Entropic (Gromov) Wasserstein Flow Matching with Applications to Single-Cell Genomics
by: Klein, Dominik, et al.
Published: (2023)

Unified Guidance for Geometry-Conditioned Molecular Generation
by: Ayadi, Sirine, et al.
Published: (2025)

Edit-Based Flow Matching for Temporal Point Processes
by: Lüdke, David, et al.
Published: (2025)

Learning Equivariant Non-Local Electron Density Functionals
by: Gao, Nicholas, et al.
Published: (2024)

Unfolding Time: Generative Modeling for Turbulent Flows in 4D
by: Saydemir, Abdullah, et al.
Published: (2024)

Provably Reliable Conformal Prediction Sets in the Presence of Data Poisoning
by: Scholten, Yan, et al.
Published: (2024)

3D Molecule Generation from Rigid Motifs via SE(3) Flows
by: Poletukhin, Roman, et al.
Published: (2026)

Mixed Models with Multiple Instance Learning
by: Engelmann, Jan P., et al.
Published: (2023)

Does Data Scaling Lead to Visual Compositional Generalization?
by: Uselis, Arnas, et al.
Published: (2025)

When Does Closeness in Distribution Imply Representational Similarity? An Identifiability Perspective
by: Nielsen, Beatrix M. G., et al.
Published: (2025)

Adversarial Attacks on Graph Neural Networks via Meta Learning
by: Zügner, Daniel, et al.
Published: (2019)

Uncertainty Estimation for Heterophilic Graphs Through the Lens of Information Theory
by: Fuchsgruber, Dominik, et al.
Published: (2025)

From Zero to Turbulence: Generative Modeling for 3D Flow Simulation
by: Lienen, Marten, et al.
Published: (2023)

One-Step Score-Based Density Ratio Estimation
by: Chen, Wei, et al.
Published: (2026)

Energy-Weighted Flow Matching: Unlocking Continuous Normalizing Flows for Efficient and Scalable Boltzmann Sampling
by: Dern, Niclas, et al.
Published: (2025)

Unbounded Density Ratio Estimation and Its Application to Covariate Shift Adaptation
by: Liu, Ren-Rui, et al.
Published: (2026)

Joint Out-of-Distribution Filtering and Data Discovery Active Learning
by: Schmidt, Sebastian, et al.
Published: (2025)

Interpolating Discrete Diffusion Models with Controllable Resampling
by: Kollovieh, Marcel, et al.
Published: (2026)

Task-Awareness Improves LLM Generations and Uncertainty
by: Tomov, Tim, et al.
Published: (2026)

UnHiPPO: Uncertainty-aware Initialization for State Space Models
by: Lienen, Marten, et al.
Published: (2025)

What Expressivity Theory Misses: Message Passing Complexity for GNNs
by: Kemper, Niklas, et al.
Published: (2025)

Generative Modeling with Bayesian Sample Inference
by: Lienen, Marten, et al.
Published: (2025)

Energy-based Epistemic Uncertainty for Graph Neural Networks
by: Fuchsgruber, Dominik, et al.
Published: (2024)

Compositional Generalization Requires Linear, Orthogonal Representations in Vision Embedding Models
by: Uselis, Arnas, et al.
Published: (2026)

Flow Matching with Gaussian Process Priors for Probabilistic Time Series Forecasting
by: Kollovieh, Marcel, et al.
Published: (2024)

On Representing Electronic Wave Functions with Sign Equivariant Neural Networks
by: Gao, Nicholas, et al.
Published: (2024)

Neural Pfaffians: Solving Many Many-Electron Schrödinger Equations
by: Gao, Nicholas, et al.
Published: (2024)

Diffusion Secant Alignment for Score-Based Density Ratio Estimation
by: Chen, Wei, et al.
Published: (2025)

Efficient Adversarial Training in LLMs with Continuous Attacks
by: Xhonneux, Sophie, et al.
Published: (2024)

Binary Losses for Density Ratio Estimation
by: Zellinger, Werner
Published: (2024)

Explicit Flow Matching: On The Theory of Flow Matching Algorithms with Applications
by: Ryzhakov, Gleb, et al.
Published: (2024)

Projection Pursuit Density Ratio Estimation
by: Wang, Meilin, et al.
Published: (2025)

A Probabilistic Perspective on Unlearning and Alignment for Large Language Models
by: Scholten, Yan, et al.
Published: (2024)

Intriguing Properties of Input-dependent Randomized Smoothing
by: Súkeník, Peter, et al.
Published: (2021)

Provable Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More
by: Schuchardt, Jan, et al.
Published: (2023)

Sparse Shift Autoencoders for Identifying Concepts from Large Language Model Activations
by: Joshi, Shruti, et al.
Published: (2025)

OmegAMP: Targeted AMP Discovery through Biologically Informed Generation
by: Soares, Diogo, et al.
Published: (2025)