:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Fadel, Samuel G., Mair, Sebastian, Torres, Ricardo da S., Brefeld, Ulf
Format:	Preprint
Published:	2020
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2010.12059
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Explaining the Impact of Training on Vision Models via Activation Clustering
by: Boubekki, Ahcène, et al.
Published: (2024)

Self-Supervised Siamese Autoencoders
by: Baier, Friederike, et al.
Published: (2023)

Archetypal Analysis++: Rethinking the Initialization Strategy
by: Mair, Sebastian, et al.
Published: (2023)

Leveraging Activations for Superpixel Explanations
by: Boubekki, Ahcène, et al.
Published: (2024)

Personalized Privacy Amplification via Importance Sampling
by: Fay, Dominik, et al.
Published: (2023)

A Survey on Archetypal Analysis
by: Alcacer, Aleix, et al.
Published: (2025)

Efficient Radiation Treatment Planning based on Voxel Importance
by: Mair, Sebastian, et al.
Published: (2024)

On Feynman--Kac training of partial Bayesian neural networks
by: Zhao, Zheng, et al.
Published: (2023)

On the Contractivity of Stochastic Interpolation Flow
by: Daniels, Mara
Published: (2025)

Gaussian Interpolation Flows
by: Gao, Yuan, et al.
Published: (2023)

Learning Straight Flows by Learning Curved Interpolants
by: Shankar, Shiv, et al.
Published: (2025)

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

Distilling Normalizing Flows
by: Walton, Steven, et al.
Published: (2025)

Preferential Normalizing Flows
by: Mikkola, Petrus, et al.
Published: (2024)

Piecewise Normalizing Flows
by: Bevins, Harry, et al.
Published: (2023)

SplineFlow: Flow Matching for Dynamical Systems with B-Spline Interpolants
by: Rathod, Santanu Subhash, et al.
Published: (2026)

Ising on the Graph: Task-specific Graph Subsampling via the Ising Model
by: Bånkestad, Maria, et al.
Published: (2024)

Multi-Marginal Flow Matching with Adversarially Learnt Interpolants
by: Kviman, Oskar, et al.
Published: (2025)

Metric Flow Matching for Smooth Interpolations on the Data Manifold
by: Kapuśniak, Kacper, et al.
Published: (2024)

Order-based Structure Learning with Normalizing Flows
by: Kamkari, Hamidreza, et al.
Published: (2023)

Flexible Tails for Normalizing Flows
by: Hickling, Tennessee, et al.
Published: (2024)

Causally Consistent Normalizing Flow
by: Zhou, Qingyang, et al.
Published: (2024)

DFM: Interpolant-free Dual Flow Matching
by: Gudovskiy, Denis, et al.
Published: (2024)

Normalizing Flows for Conformal Regression
by: Colombo, Nicolo
Published: (2024)

Normalizing Flows are Capable Models for RL
by: Ghugare, Raj, et al.
Published: (2025)

Gradual Domain Adaptation via Normalizing Flows
by: Sagawa, Shogo, et al.
Published: (2022)

Multivariate Latent Recalibration for Conditional Normalizing Flows
by: Dheur, Victor, et al.
Published: (2025)

Free-form Flows: Make Any Architecture a Normalizing Flow
by: Draxler, Felix, et al.
Published: (2023)

IN-Flow: Instance Normalization Flow for Non-stationary Time Series Forecasting
by: Fan, Wei, et al.
Published: (2024)

BézierFlow: Learning Bézier Stochastic Interpolant Schedulers for Few-Step Generation
by: Min, Yunhong, et al.
Published: (2025)

MolPIF: A Parameter Interpolation Flow Model for Molecule Generation
by: Jin, Yaowei, et al.
Published: (2025)

Markovian Flow Matching: Accelerating MCMC with Continuous Normalizing Flows
by: Cabezas, Alberto, et al.
Published: (2024)

Position: Stop Preaching and Start Practising Data Frugality for Responsible Development of AI
by: Wilson, Sophia N., et al.
Published: (2026)

Amortized Sampling with Transferable Normalizing Flows
by: Tan, Charlie B., et al.
Published: (2025)

Quantum Normalizing Flows for Anomaly Detection
by: Rosenhahn, Bodo, et al.
Published: (2024)

Knowledge Graph Embedding by Normalizing Flows
by: Xiao, Changyi, et al.
Published: (2024)

Combining Normalizing Flows and Quasi-Monte Carlo
by: Andral, Charly
Published: (2024)

FlowVAT: Normalizing Flow Variational Inference with Affine-Invariant Tempering
by: Qin, Juehang, et al.
Published: (2025)

FlowSDR: Sufficient Dimension Reduction via Conditional Normalizing Flows
by: Dong, Yuexiao, et al.
Published: (2026)

PolicyFlow: Policy Optimization with Continuous Normalizing Flow in Reinforcement Learning
by: Yang, Shunpeng, et al.
Published: (2026)