Disentangling impact of capacity, objective, batchsize, estimators, and step-size on flow VI
Fuente:
arXiv
Saved in:
| Main Authors: | Agrawal, Abhinav, Domke, Justin |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Understanding and mitigating difficulties in posterior predictive evaluation
by: Agrawal, Abhinav, et al.
Published: (2024)
by: Agrawal, Abhinav, et al.
Published: (2024)
Large Language Bayes
by: Domke, Justin
Published: (2025)
by: Domke, Justin
Published: (2025)
Model-Informed Flows for Bayesian Inference
by: Ko, Joohwan, et al.
Published: (2025)
by: Ko, Joohwan, et al.
Published: (2025)
Amortized Factor Inference Networks for Posterior Inference
by: Ko, Joohwan, et al.
Published: (2026)
by: Ko, Joohwan, et al.
Published: (2026)
Hamiltonian Monte Carlo Inference of Marginalized Linear Mixed-Effects Models
by: Lai, Jinlin, et al.
Published: (2024)
by: Lai, Jinlin, et al.
Published: (2024)
Joint control variate for faster black-box variational inference
by: Wang, Xi, et al.
Published: (2022)
by: Wang, Xi, et al.
Published: (2022)
New allometric models for the USA create a step-change in forest carbon estimation, modeling, and mapping
by: Johnson, Lucas K., et al.
Published: (2024)
by: Johnson, Lucas K., et al.
Published: (2024)
Simulation-based stacking
by: Yao, Yuling, et al.
Published: (2023)
by: Yao, Yuling, et al.
Published: (2023)
Sparse Polyak: an adaptive step size rule for high-dimensional M-estimation
by: Qiao, Tianqi, et al.
Published: (2025)
by: Qiao, Tianqi, et al.
Published: (2025)
Online conformal prediction with decaying step sizes
by: Angelopoulos, Anastasios N., et al.
Published: (2024)
by: Angelopoulos, Anastasios N., et al.
Published: (2024)
Physics-informed neural particle flow for the Bayesian update step
by: Csuzdi, Domonkos, et al.
Published: (2026)
by: Csuzdi, Domonkos, et al.
Published: (2026)
$α$-TCVAE: On the relationship between Disentanglement and Diversity
by: Meo, Cristian, et al.
Published: (2024)
by: Meo, Cristian, et al.
Published: (2024)
Painless step size adaptation for SGD
by: Kulikovskikh, Ilona, et al.
Published: (2021)
by: Kulikovskikh, Ilona, et al.
Published: (2021)
New logarithmic step size for stochastic gradient descent
by: Shamaee, M. Soheil, et al.
Published: (2024)
by: Shamaee, M. Soheil, et al.
Published: (2024)
Shuffling the Data, Stretching the Step-size: Sharper Bias in constant step-size SGD
by: Emmanouilidis, Konstantinos, et al.
Published: (2026)
by: Emmanouilidis, Konstantinos, et al.
Published: (2026)
Optimistic Q-learning for average reward and episodic reinforcement learning
by: Agrawal, Priyank, et al.
Published: (2024)
by: Agrawal, Priyank, et al.
Published: (2024)
One-step corrected projected stochastic gradient descent for statistical estimation
by: Brouste, Alexandre, et al.
Published: (2023)
by: Brouste, Alexandre, et al.
Published: (2023)
KANITE: Kolmogorov-Arnold Networks for ITE estimation
by: Mehendale, Eshan, et al.
Published: (2025)
by: Mehendale, Eshan, et al.
Published: (2025)
Motor Vehicle Accident Severity Prediction Via Machine Learning
by: Chandolu, Abhinav
Published: (2025)
by: Chandolu, Abhinav
Published: (2025)
CRAUM-Net: Contextual Recursive Attention with Uncertainty Modeling for Salient Object Detection
by: Sagar, Abhinav
Published: (2020)
by: Sagar, Abhinav
Published: (2020)
Q-learning with Posterior Sampling
by: Agrawal, Priyank, et al.
Published: (2025)
by: Agrawal, Priyank, et al.
Published: (2025)
Convergence and concentration properties of constant step-size SGD through Markov chains
by: Merad, Ibrahim, et al.
Published: (2023)
by: Merad, Ibrahim, et al.
Published: (2023)
BEACON: Bayesian Experimental design Acceleration with Conditional Normalizing flows $-$ a case study in optimal monitor well placement for CO$_2$ sequestration
by: Orozco, Rafael, et al.
Published: (2024)
by: Orozco, Rafael, et al.
Published: (2024)
Operationalizing Quantized Disentanglement
by: Barin-Pacela, Vitoria, et al.
Published: (2025)
by: Barin-Pacela, Vitoria, et al.
Published: (2025)
Convergence rates of stochastic gradient method with independent sequences of step-size and momentum weight
by: Hwang, Wen-Liang
Published: (2024)
by: Hwang, Wen-Liang
Published: (2024)
Glocal Smoothness: Line search and adaptive step sizes can help in theory too!
by: Fox, Curtis, et al.
Published: (2025)
by: Fox, Curtis, et al.
Published: (2025)
Convergence of projected stochastic natural gradient variational inference for various step size and sample or batch size schedules
by: Guilmeau, Thomas, et al.
Published: (2026)
by: Guilmeau, Thomas, et al.
Published: (2026)
PINP: Physics-Informed Neural Predictor with latent estimation of fluid flows
by: Chen, Huaguan, et al.
Published: (2025)
by: Chen, Huaguan, 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)
VQ-Style: Disentangling Style and Content in Motion with Residual Quantized Representations
by: Zargarbashi, Fatemeh, et al.
Published: (2026)
by: Zargarbashi, Fatemeh, et al.
Published: (2026)
Machine Learning Hamiltonian Dynamical Systems with Sparse and Noisy Data
by: Thapar, Vedanta, et al.
Published: (2026)
by: Thapar, Vedanta, et al.
Published: (2026)
Variational Learning of Disentangled Representations
by: Slavutsky, Yuli, et al.
Published: (2025)
by: Slavutsky, Yuli, et al.
Published: (2025)
Disentangled Interleaving Variational Encoding
by: Wong, Noelle Y. L., et al.
Published: (2025)
by: Wong, Noelle Y. L., et al.
Published: (2025)
Supervised Contrastive Block Disentanglement
by: Makino, Taro, et al.
Published: (2025)
by: Makino, Taro, et al.
Published: (2025)
Efficiently Disentangle Causal Representations
by: Li, Yuanpeng, et al.
Published: (2022)
by: Li, Yuanpeng, et al.
Published: (2022)
On the optimization dynamics of RLVR: Gradient gap and step size thresholds
by: Suk, Joe, et al.
Published: (2025)
by: Suk, Joe, et al.
Published: (2025)
Lookbehind-SAM: k steps back, 1 step forward
by: Mordido, Gonçalo, et al.
Published: (2023)
by: Mordido, Gonçalo, et al.
Published: (2023)
Normalizing flow-based deep variational Bayesian network for seismic multi-hazards and impacts estimation from InSAR imagery
by: Li, Xuechun, et al.
Published: (2023)
by: Li, Xuechun, et al.
Published: (2023)
Structural Disentanglement of Causal and Correlated Concepts
by: Zhao, Qilong, et al.
Published: (2024)
by: Zhao, Qilong, et al.
Published: (2024)
Disentangling Dense Embeddings with Sparse Autoencoders
by: O'Neill, Charles, et al.
Published: (2024)
by: O'Neill, Charles, et al.
Published: (2024)
Similar Items
-
Understanding and mitigating difficulties in posterior predictive evaluation
by: Agrawal, Abhinav, et al.
Published: (2024) -
Large Language Bayes
by: Domke, Justin
Published: (2025) -
Model-Informed Flows for Bayesian Inference
by: Ko, Joohwan, et al.
Published: (2025) -
Amortized Factor Inference Networks for Posterior Inference
by: Ko, Joohwan, et al.
Published: (2026) -
Hamiltonian Monte Carlo Inference of Marginalized Linear Mixed-Effects Models
by: Lai, Jinlin, et al.
Published: (2024)