Flows and Diffusions on the Neural Manifold
Fuente:
arXiv
Saved in:
| Main Authors: | Saragih, Daniel, Cao, Deyu, Balaji, Tejas |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Flow to Learn: Flow Matching on Neural Network Parameters
by: Saragih, Daniel, et al.
Published: (2025)
by: Saragih, Daniel, et al.
Published: (2025)
Augmented Equivariant Mesh Networks for Anatomical Segmentation
by: Saragih, Daniel
Published: (2026)
by: Saragih, Daniel
Published: (2026)
Improving Shift Invariance in Convolutional Neural Networks with Translation Invariant Polyphase Sampling
by: Saha, Sourajit, et al.
Published: (2024)
by: Saha, Sourajit, et al.
Published: (2024)
Side Effects of Erasing Concepts from Diffusion Models
by: Saha, Shaswati, et al.
Published: (2025)
by: Saha, Shaswati, et al.
Published: (2025)
Neural Flow Diffusion Models: Learnable Forward Process for Improved Diffusion Modelling
by: Bartosh, Grigory, et al.
Published: (2024)
by: Bartosh, Grigory, et al.
Published: (2024)
ManifoldGD: Training-Free Hierarchical Manifold Guidance for Diffusion-Based Dataset Distillation
by: Roy, Ayush, et al.
Published: (2026)
by: Roy, Ayush, et al.
Published: (2026)
CoordFlow: Coordinate Flow for Pixel-wise Neural Video Representation
by: Silver, Daniel, et al.
Published: (2025)
by: Silver, Daniel, et al.
Published: (2025)
Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders
by: Kumar, Amandeep, et al.
Published: (2026)
by: Kumar, Amandeep, et al.
Published: (2026)
Derivative-Free Diffusion Manifold-Constrained Gradient for Unified XAI
by: Kim, Won Jun, et al.
Published: (2024)
by: Kim, Won Jun, et al.
Published: (2024)
ConceptBed: Evaluating Concept Learning Abilities of Text-to-Image Diffusion Models
by: Patel, Maitreya, et al.
Published: (2023)
by: Patel, Maitreya, et al.
Published: (2023)
Straighter Flow Matching via a Diffusion-Based Coupling Prior
by: Xing, Siyu, et al.
Published: (2023)
by: Xing, Siyu, et al.
Published: (2023)
Varying Manifolds in Diffusion: From Time-varying Geometries to Visual Saliency
by: Chen, Junhao, et al.
Published: (2024)
by: Chen, Junhao, et al.
Published: (2024)
The Deepfake Detective: Interpreting Neural Forensics Through Sparse Features and Manifolds
by: Sahoo, Subramanyam, et al.
Published: (2025)
by: Sahoo, Subramanyam, et al.
Published: (2025)
Optimizing CNN Architectures for Advanced Thoracic Disease Classification
by: Mirthipati, Tejas
Published: (2025)
by: Mirthipati, Tejas
Published: (2025)
Ensemble everything everywhere: Multi-scale aggregation for adversarial robustness
by: Fort, Stanislav, et al.
Published: (2024)
by: Fort, Stanislav, et al.
Published: (2024)
Measuring Feature Dependency of Neural Networks by Collapsing Feature Dimensions in the Data Manifold
by: Jin, Yinzhu, et al.
Published: (2024)
by: Jin, Yinzhu, et al.
Published: (2024)
Understanding Dataset Distillation via Spectral Filtering
by: Bo, Deyu, et al.
Published: (2025)
by: Bo, Deyu, et al.
Published: (2025)
Exploring Time Conditioning in Diffusion Generative Models from Disjoint Noisy Data Manifolds
by: Li, Liuzhuozheng, et al.
Published: (2026)
by: Li, Liuzhuozheng, et al.
Published: (2026)
Harnessing Data Asymmetry: Manifold Learning in the Finsler World
by: Dagès, Thomas, et al.
Published: (2026)
by: Dagès, Thomas, et al.
Published: (2026)
Neural Network Diffusion
by: Wang, Kai, et al.
Published: (2024)
by: Wang, Kai, et al.
Published: (2024)
CreativeVR: Diffusion-Prior-Guided Approach for Structure and Motion Restoration in Generative and Real Videos
by: Panambur, Tejas, et al.
Published: (2025)
by: Panambur, Tejas, et al.
Published: (2025)
What's Inside Your Diffusion Model? A Score-Based Riemannian Metric to Explore the Data Manifold
by: Azeglio, Simone, et al.
Published: (2025)
by: Azeglio, Simone, et al.
Published: (2025)
Flow Equivariant Recurrent Neural Networks
by: Keller, T. Anderson
Published: (2025)
by: Keller, T. Anderson
Published: (2025)
Lyapunov Stable Graph Neural Flow
by: Chu, Haoyu, et al.
Published: (2026)
by: Chu, Haoyu, et al.
Published: (2026)
Universal Facial Encoding of Codec Avatars from VR Headsets
by: Bai, Shaojie, et al.
Published: (2024)
by: Bai, Shaojie, et al.
Published: (2024)
Feed Two Birds with One Scone: Exploiting Function-Space Regularization for Both OOD Robustness and ID Fine-Tuning Performance
by: Yuan, Xiang, et al.
Published: (2025)
by: Yuan, Xiang, et al.
Published: (2025)
Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment
by: Schusterbauer, Johannes, et al.
Published: (2025)
by: Schusterbauer, Johannes, et al.
Published: (2025)
PICS in Pics: Physics Informed Contour Selection for Rapid Image Segmentation
by: Dwivedi, Vikas, et al.
Published: (2023)
by: Dwivedi, Vikas, et al.
Published: (2023)
Neuroexplicit Diffusion Models for Inpainting of Optical Flow Fields
by: Fischer, Tom, et al.
Published: (2024)
by: Fischer, Tom, et al.
Published: (2024)
Exploring Diffusion and Flow Matching Under Generator Matching
by: Patel, Zeeshan, et al.
Published: (2024)
by: Patel, Zeeshan, et al.
Published: (2024)
Manifold Learning for Hyperspectral Images
by: Harkat, Fethi, et al.
Published: (2025)
by: Harkat, Fethi, et al.
Published: (2025)
Understanding Generalization in Diffusion Distillation via Probability Flow Distance
by: Zhang, Huijie, et al.
Published: (2025)
by: Zhang, Huijie, et al.
Published: (2025)
On the Design of One-step Diffusion via Shortcutting Flow Paths
by: Lin, Haitao, et al.
Published: (2025)
by: Lin, Haitao, et al.
Published: (2025)
Large Scale Diffusion Distillation via Score-Regularized Continuous-Time Consistency
by: Zheng, Kaiwen, et al.
Published: (2025)
by: Zheng, Kaiwen, et al.
Published: (2025)
The Manifold Hypothesis for Gradient-Based Explanations
by: Bordt, Sebastian, et al.
Published: (2022)
by: Bordt, Sebastian, et al.
Published: (2022)
CFG++: Manifold-constrained Classifier Free Guidance for Diffusion Models
by: Chung, Hyungjin, et al.
Published: (2024)
by: Chung, Hyungjin, et al.
Published: (2024)
Improving Diffusion Models for Inverse Problems using Manifold Constraints
by: Chung, Hyungjin, et al.
Published: (2022)
by: Chung, Hyungjin, et al.
Published: (2022)
From Diffusion to Flow: Efficient Motion Generation in MotionGPT3
by: Ban, Jaymin, et al.
Published: (2026)
by: Ban, Jaymin, et al.
Published: (2026)
Generalization and Memorization in Rectified Flow
by: Rao, Mingxing, et al.
Published: (2026)
by: Rao, Mingxing, et al.
Published: (2026)
Multi-conditioned Graph Diffusion for Neural Architecture Search
by: Asthana, Rohan, et al.
Published: (2024)
by: Asthana, Rohan, et al.
Published: (2024)
Similar Items
-
Flow to Learn: Flow Matching on Neural Network Parameters
by: Saragih, Daniel, et al.
Published: (2025) -
Augmented Equivariant Mesh Networks for Anatomical Segmentation
by: Saragih, Daniel
Published: (2026) -
Improving Shift Invariance in Convolutional Neural Networks with Translation Invariant Polyphase Sampling
by: Saha, Sourajit, et al.
Published: (2024) -
Side Effects of Erasing Concepts from Diffusion Models
by: Saha, Shaswati, et al.
Published: (2025) -
Neural Flow Diffusion Models: Learnable Forward Process for Improved Diffusion Modelling
by: Bartosh, Grigory, et al.
Published: (2024)