Saved in:
| Main Authors: | Ganguli, Arkaprabha, Ramachandra, Nesar, Bessac, Julie, Constantinescu, Emil |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.00298 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Uncovering Physical Drivers of Dark Matter Halo Structures with Auxiliary-Variable-Guided Generative Models
by: Ganguli, Arkaprabha, et al.
Published: (2026)
by: Ganguli, Arkaprabha, et al.
Published: (2026)
Disentangled Deep Priors for Bayesian Inverse Problems
by: Ganguli, Arkaprabha, et al.
Published: (2026)
by: Ganguli, Arkaprabha, et al.
Published: (2026)
Summary Statistics of Large-scale Model Outputs for Observation-corrected Outputs
by: Chakraborty, Atlanta, et al.
Published: (2025)
by: Chakraborty, Atlanta, et al.
Published: (2025)
Multi-modal Bayesian Neural Network Surrogates with Conjugate Last-Layer Estimation
by: Taylor, Ian, et al.
Published: (2025)
by: Taylor, Ian, et al.
Published: (2025)
Latent Space Disentanglement via Activation Steering for Interpretable Attribute Control in Symbolic Music Generation
by: Prokopiou, Ioannis, et al.
Published: (2026)
by: Prokopiou, Ioannis, et al.
Published: (2026)
Distributional Sensitivity Analysis: Enabling Differentiability in Sample-Based Inference
by: Chuang, Pi-Yueh, et al.
Published: (2025)
by: Chuang, Pi-Yueh, et al.
Published: (2025)
Differentiable DG with Neural Operator Source Term Correction
by: Kang, Shinhoo, et al.
Published: (2023)
by: Kang, Shinhoo, et al.
Published: (2023)
Reflections on Disentanglement and the Latent Space
by: Schaerf, Ludovica
Published: (2024)
by: Schaerf, Ludovica
Published: (2024)
Improving the Predictability of the Madden-Julian Oscillation at Subseasonal Scales with Gaussian Process Models
by: Chen, Haoyuan, et al.
Published: (2025)
by: Chen, Haoyuan, et al.
Published: (2025)
Multidimensional Distributional Neural Network Output Demonstrated in Super-Resolution of Surface Wind Speed
by: Goldwyn, Harrison J., et al.
Published: (2025)
by: Goldwyn, Harrison J., et al.
Published: (2025)
Disentangled Latent Spaces for Reduced Order Models using Deterministic Autoencoders
by: Schwarz, Henning, et al.
Published: (2025)
by: Schwarz, Henning, et al.
Published: (2025)
CTTVAE: Latent Space Structuring for Conditional Tabular Data Generation on Imbalanced Datasets
by: Devic, Milosh, et al.
Published: (2026)
by: Devic, Milosh, et al.
Published: (2026)
SynMorph: Generating Synthetic Face Morphing Dataset with Mated Samples
by: Zhang, Haoyu, et al.
Published: (2024)
by: Zhang, Haoyu, et al.
Published: (2024)
Compositional Generalization via Forced Rendering of Disentangled Latents
by: Liang, Qiyao, et al.
Published: (2025)
by: Liang, Qiyao, et al.
Published: (2025)
A Unified Latent Space Disentanglement VAE Framework with Robust Disentanglement Effectiveness Evaluation
by: Lang, Xiaoan, et al.
Published: (2026)
by: Lang, Xiaoan, et al.
Published: (2026)
Interpretable Generalized Additive Models for Datasets with Missing Values
by: McTavish, Hayden, et al.
Published: (2024)
by: McTavish, Hayden, et al.
Published: (2024)
Disentangled Latent Spaces Facilitate Data-Driven Auxiliary Learning
by: Skenderi, Geri, et al.
Published: (2023)
by: Skenderi, Geri, et al.
Published: (2023)
Isometric Representation Learning for Disentangled Latent Space of Diffusion Models
by: Hahm, Jaehoon, et al.
Published: (2024)
by: Hahm, Jaehoon, et al.
Published: (2024)
Streaming Operator Inference for Model Reduction of Large-Scale Dynamical Systems
by: Koike, Tomoki, et al.
Published: (2026)
by: Koike, Tomoki, et al.
Published: (2026)
Sculpting Latent Spaces With MMD: Disentanglement With Programmable Priors
by: Fruytier, Quentin, et al.
Published: (2025)
by: Fruytier, Quentin, et al.
Published: (2025)
Multi-task Modeling for Engineering Applications with Sparse Data
by: Comlek, Yigitcan, et al.
Published: (2026)
by: Comlek, Yigitcan, et al.
Published: (2026)
Gradient-Guided Exploration of Generative Model's Latent Space for Controlled Iris Image Augmentations
by: Mitcheff, Mahsa, et al.
Published: (2025)
by: Mitcheff, Mahsa, et al.
Published: (2025)
Diffusion-Based Generation of Neural Activity from Disentangled Latent Codes
by: McCart, Jonathan D., et al.
Published: (2024)
by: McCart, Jonathan D., et al.
Published: (2024)
Image and Video Quality Assessment using Prompt-Guided Latent Diffusion Models for Cross-Dataset Generalization
by: Mitra, Shankhanil, et al.
Published: (2024)
by: Mitra, Shankhanil, et al.
Published: (2024)
Latent Space Factorization in LoRA
by: Kumar, Shashi, et al.
Published: (2025)
by: Kumar, Shashi, et al.
Published: (2025)
Enhancing Interpretability Through Loss-Defined Classification Objective in Structured Latent Spaces
by: Geissler, Daniel, et al.
Published: (2024)
by: Geissler, Daniel, et al.
Published: (2024)
Aircraft Trajectory Dataset Augmentation in Latent Space
by: Yoon, Seokbin, et al.
Published: (2025)
by: Yoon, Seokbin, et al.
Published: (2025)
Less Is More: Generating Time Series with LLaMA-Style Autoregression in Simple Factorized Latent Spaces
by: Li, Siyuan, et al.
Published: (2025)
by: Li, Siyuan, et al.
Published: (2025)
On Robust Cross Domain Alignment
by: Chakrabarty, Anish, et al.
Published: (2024)
by: Chakrabarty, Anish, et al.
Published: (2024)
Disentangling Interpretable Factors with Supervised Independent Subspace Principal Component Analysis
by: Su, Jiayu, et al.
Published: (2024)
by: Su, Jiayu, et al.
Published: (2024)
Exploring Representation-Aligned Latent Space for Better Generation
by: Xu, Wanghan, et al.
Published: (2025)
by: Xu, Wanghan, et al.
Published: (2025)
Advancing Generalization in PINNs through Latent-Space Representations
by: Wang, Honghui, et al.
Published: (2024)
by: Wang, Honghui, et al.
Published: (2024)
Shortcut Invariance: Targeted Jacobian Regularization in Disentangled Latent Space
by: Pal, Shivam, et al.
Published: (2025)
by: Pal, Shivam, et al.
Published: (2025)
Multi-Objective Latent Space Optimization of Generative Molecular Design Models
by: Abeer, A N M Nafiz, et al.
Published: (2022)
by: Abeer, A N M Nafiz, et al.
Published: (2022)
Lossless Compression for LLM Tensor Incremental Snapshots
by: Waddington, Daniel, et al.
Published: (2025)
by: Waddington, Daniel, et al.
Published: (2025)
Differentiable Autoencoding Neural Operator for Interpretable and Integrable Latent Space Modeling
by: Viknesh, Siva, et al.
Published: (2025)
by: Viknesh, Siva, et al.
Published: (2025)
TFGN: Task-Free, Replay-Free Continual Pre-Training Without Catastrophic Forgetting at LLM Scale
by: Ganguli, Anurup
Published: (2026)
by: Ganguli, Anurup
Published: (2026)
EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling
by: Kouzelis, Theodoros, et al.
Published: (2025)
by: Kouzelis, Theodoros, et al.
Published: (2025)
Disentanglement of Biological and Technical Factors via Latent Space Rotation in Clinical Imaging Improves Disease Pattern Discovery
by: Pan, Jeanny, et al.
Published: (2025)
by: Pan, Jeanny, et al.
Published: (2025)
Discovering Interpretable Directions in the Semantic Latent Space of Diffusion Models
by: Haas, René, et al.
Published: (2023)
by: Haas, René, et al.
Published: (2023)
Similar Items
-
Uncovering Physical Drivers of Dark Matter Halo Structures with Auxiliary-Variable-Guided Generative Models
by: Ganguli, Arkaprabha, et al.
Published: (2026) -
Disentangled Deep Priors for Bayesian Inverse Problems
by: Ganguli, Arkaprabha, et al.
Published: (2026) -
Summary Statistics of Large-scale Model Outputs for Observation-corrected Outputs
by: Chakraborty, Atlanta, et al.
Published: (2025) -
Multi-modal Bayesian Neural Network Surrogates with Conjugate Last-Layer Estimation
by: Taylor, Ian, et al.
Published: (2025) -
Latent Space Disentanglement via Activation Steering for Interpretable Attribute Control in Symbolic Music Generation
by: Prokopiou, Ioannis, et al.
Published: (2026)