Injective flows for star-like manifolds

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Negri, Marcello Massimo, Aellen, Jonathan, Roth, Volker
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Marginal Flow: a flexible and efficient framework for density estimation
by: Negri, Marcello Massimo, et al.
Published: (2025)

NIMO: a Nonlinear Interpretable MOdel
by: Xu, Shijian, et al.
Published: (2025)

Lifting Architectural Constraints of Injective Flows
by: Sorrenson, Peter, et al.
Published: (2023)

Bi-Lipschitz Autoencoder With Injectivity Guarantee
by: Zhan, Qipeng, et al.
Published: (2026)

Language Models are Injective and Hence Invertible
by: Nikolaou, Giorgos, et al.
Published: (2025)

Injectivity of ReLU-layers: Tools from Frame Theory
by: Haider, Daniel, et al.
Published: (2024)

On the (Non) Injectivity of Piecewise Linear Janossy Pooling
by: Reshef, Ilai, et al.
Published: (2025)

Simple, Fast and Efficient Injective Manifold Density Estimation with Random Projections
by: Amin, Ahmad Ayaz, et al.
Published: (2025)

Inverting Non-Injective Functions with Twin Neural Network Regression
by: Wetzel, Sebastian J.
Published: (2026)

Injectivity capacity of ReLU gates
by: Stojnic, Mihailo
Published: (2024)

Beyond Diagonal Covariance: Flexible Posterior VAEs via Free-Form Injective Flows
by: Sorrenson, Peter, et al.
Published: (2025)

Complexity of Injectivity and Verification of ReLU Neural Networks
by: Froese, Vincent, et al.
Published: (2024)

Sharpness-Aware Poisoning: Enhancing Transferability of Injective Attacks on Recommender Systems
by: Xie, Junsong, et al.
Published: (2026)

On the Injective Norm of Sums of Random Tensors and the Moments of Gaussian Chaoses
by: Aden-Ali, Ishaq
Published: (2025)

Physics-Informed Boundary Integral Networks (PIBI-Nets): A Data-Driven Approach for Solving Partial Differential Equations
by: Nagy-Huber, Monika, et al.
Published: (2023)

Can we ease the Injectivity Bottleneck on Lorentzian Manifolds for Graph Neural Networks?
by: Srinivasan, Srinitish, et al.
Published: (2025)

Canonical normalizing flows for manifold learning
by: Flouris, Kyriakos, et al.
Published: (2023)

Injectivity of ReLU networks: perspectives from statistical physics
by: Maillard, Antoine, et al.
Published: (2023)

Transformer Injectivity & Geometric Robustness - Analytic Margins and Bi-Lipschitz Uniformity of Sequence-Level Hidden States
by: von Strauss, Mikael
Published: (2025)

Fault injection analysis of Real NVP normalising flow model for satellite anomaly detection
by: Greco, Gabriele, et al.
Published: (2025)

On the geometry and topology of representations: the manifolds of modular addition
by: Moisescu-Pareja, Gabriela, et al.
Published: (2025)

Simplifying the Theory on Over-Smoothing
by: Roth, Andreas
Published: (2024)

Which Leakage Types Matter? A Quantitative Landscape Across 2,047 Benchmark Datasets
by: Roth, Simon
Published: (2026)

Towards Understanding and Avoiding Limitations of Convolutions on Graphs
by: Roth, Andreas
Published: (2026)

Building symmetries into data-driven manifold dynamics models for complex flows: application to two-dimensional Kolmogorov flow
by: De Jesús, Carlos E. Pérez, et al.
Published: (2023)

Learning on manifolds without manifold learning
by: Mhaskar, H. N., et al.
Published: (2024)

Out-of-distribution detection using normalizing flows on the data manifold
by: Razavi, Seyedeh Fatemeh, et al.
Published: (2023)

ETHER: Efficient Finetuning of Large-Scale Models with Hyperplane Reflections
by: Bini, Massimo, et al.
Published: (2024)

Self-attention as an attractor network: transient memories without backpropagation
by: D'Amico, Francesco, et al.
Published: (2024)

Fisher-Bingham-like normalizing flows on the sphere
by: Glüsenkamp, Thorsten
Published: (2025)

ULF: Unsupervised Labeling Function Correction using Cross-Validation for Weak Supervision
by: Sedova, Anastasiia, et al.
Published: (2022)

What Can We Learn From MIMO Graph Convolutions?
by: Roth, Andreas, et al.
Published: (2025)

Finite Sample Bounds for Non-Parametric Regression: Optimal Sample Efficiency and Space Complexity
by: Maran, Davide, et al.
Published: (2024)

Online Market Making and the Value of Observing the Order Book
by: Maran, Davide, et al.
Published: (2026)

Networks with Finite VC Dimension: Pro and Contra
by: Kurkova, Vera, et al.
Published: (2025)

Online Dynamic Pricing of Complementary Products
by: Mussi, Marco, et al.
Published: (2025)

Combining Wasserstein-1 and Wasserstein-2 proximals: robust manifold learning via well-posed generative flows
by: Gu, Hyemin, et al.
Published: (2024)

LE BAGUEMENT DES CHAUVES-SOURIS AU COL DE BKETOLET (VALAIS)
by: Aellen, V
Published: (1962)

Implicit bias produces neural scaling laws in learning curves, from perceptrons to deep networks
by: D'Amico, Francesco, et al.
Published: (2025)

Gower's similarity coefficients with automatic weight selection
by: D'Orazio, Marcello
Published: (2024)