"normalizing flows" Papers
20 papers found
Amortized Sampling with Transferable Normalizing Flows
Charlie Tan, Majdi Hassan, Leon Klein et al.
Causally Consistent Normalizing Flow
Qingyang Zhou, Kangjie Lu, Meng Xu
CDFlow: Building Invertible Layers with Circulant and Diagonal Matrices
XUCHEN FENG, Siyu Liao
Detecting Generated Images by Fitting Natural Image Distributions
Yonggang Zhang, Jun Nie, Xinmei Tian et al.
Enhanced Importance Sampling Through Latent Space Exploration in Normalizing Flows
Liam Anthony Kruse, Alexandros Tzikas, Harrison Delecki et al.
Flow-based Variational Mutual Information: Fast and Flexible Approximations
Caleb Dahlke, Jason Pacheco
Inductive Domain Transfer In Misspecified Simulation-Based Inference
Ortal Senouf, Antoine Wehenkel, Cédric Vincent-Cuaz et al.
Injective flows for star-like manifolds
Marcello Negri, Jonathan Aellen, Volker Roth
Normalizing Flows are Capable Models for Continuous Control
Raj Ghugare, Benjamin Eysenbach
Partial Information Decomposition via Normalizing Flows in Latent Gaussian Distributions
Wenyuan Zhao, Adithya Balachandran, Chao Tian et al.
Path Gradients after Flow Matching
Lorenz Vaitl, Leon Klein
STARFlow: Scaling Latent Normalizing Flows for High-resolution Image Synthesis
Jiatao Gu, Tianrong Chen, David Berthelot et al.
TensoFlow: Tensorial Flow-based Sampler for Inverse Rendering
Chun Gu, Xiaofei Wei, Li Zhang et al.
Transformers for Mixed-type Event Sequences
Felix Draxler, Yang Meng, Kai Nelson et al.
A Geometric Explanation of the Likelihood OOD Detection Paradox
Hamidreza Kamkari, Brendan Ross, Jesse Cresswell et al.
Conditional Normalizing Flows for Active Learning of Coarse-Grained Molecular Representations
Henrik Schopmans, Pascal Friederich
Learning Exceptional Subgroups by End-to-End Maximizing KL-Divergence
Sascha Xu, Nils Philipp Walter, Janis Kalofolias et al.
On the Universality of Volume-Preserving and Coupling-Based Normalizing Flows
Felix Draxler, Stefan Wahl, Christoph Schnörr et al.
Robust Inverse Graphics via Probabilistic Inference
Tuan Anh Le, Pavel Sountsov, Matthew Hoffman et al.
Sequential Representation Learning via Static-Dynamic Conditional Disentanglement
Mathieu Simon, Pascal Frossard, Christophe De Vleeschouwer