Forward $χ^2$ Divergence Based Variational Importance Sampling
Fuente:
arXiv
Saved in:
| Main Authors: | Li, Chengrui, Wang, Yule, Li, Weihan, Wu, Anqi |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Differentiable Partially Observable Generalized Linear Model with Forward-Backward Message Passing
by: Li, Chengrui, et al.
Published: (2024)
by: Li, Chengrui, et al.
Published: (2024)
Exploring Behavior-Relevant and Disentangled Neural Dynamics with Generative Diffusion Models
by: Wang, Yule, et al.
Published: (2024)
by: Wang, Yule, et al.
Published: (2024)
Learning Time-Varying Multi-Region Brain Communications via Scalable Markovian Gaussian Processes
by: Li, Weihan, et al.
Published: (2024)
by: Li, Weihan, et al.
Published: (2024)
Multi-Region Markovian Gaussian Process: An Efficient Method to Discover Directional Communications Across Multiple Brain Regions
by: Li, Weihan, et al.
Published: (2024)
by: Li, Weihan, et al.
Published: (2024)
Uncovering Semantic Selectivity of Latent Groups in Higher Visual Cortex with Mutual Information-Guided Diffusion
by: Wang, Yule, et al.
Published: (2025)
by: Wang, Yule, et al.
Published: (2025)
A Revisit of Total Correlation in Disentangled Variational Auto-Encoder with Partial Disentanglement
by: Li, Chengrui, et al.
Published: (2025)
by: Li, Chengrui, et al.
Published: (2025)
A Disentangled Low-Rank RNN Framework for Uncovering Neural Connectivity and Dynamics
by: Li, Chengrui, et al.
Published: (2025)
by: Li, Chengrui, et al.
Published: (2025)
Extraction and Recovery of Spatio-Temporal Structure in Latent Dynamics Alignment with Diffusion Models
by: Wang, Yule, et al.
Published: (2023)
by: Wang, Yule, et al.
Published: (2023)
Learning When to Look: On-Demand Keypoint-Video Fusion for Animal Behavior Analysis
by: Li, Weihan, et al.
Published: (2026)
by: Li, Weihan, et al.
Published: (2026)
DISA: Offline Importance Sampling for Distribution-Matching LLM-RL
by: Wang, Shaobo, et al.
Published: (2026)
by: Wang, Shaobo, et al.
Published: (2026)
Importance Sampling for Multi-Negative Multimodal Direct Preference Optimization
by: Li, Xintong, et al.
Published: (2025)
by: Li, Xintong, et al.
Published: (2025)
Pareto Smoothed Importance Sampling
by: Vehtari, Aki, et al.
Published: (2015)
by: Vehtari, Aki, et al.
Published: (2015)
Importance is Important: Generalized Markov Chain Importance Sampling Methods
by: Li, Guanxun, et al.
Published: (2023)
by: Li, Guanxun, et al.
Published: (2023)
Federated Graph Learning with Adaptive Importance-based Sampling
by: Li, Anran, et al.
Published: (2024)
by: Li, Anran, et al.
Published: (2024)
An Adaptive Importance Sampling for Locally Stable Point Processes
by: Kang, Hee-Geon, et al.
Published: (2024)
by: Kang, Hee-Geon, et al.
Published: (2024)
DBR: Divergence-Based Regularization for Debiasing Natural Language Understanding Models
by: Li, Zihao, et al.
Published: (2025)
by: Li, Zihao, et al.
Published: (2025)
Square$χ$PO: Differentially Private and Robust $χ^2$-Preference Optimization in Offline Direct Alignment
by: Zhou, Xingyu, et al.
Published: (2025)
by: Zhou, Xingyu, et al.
Published: (2025)
Differentiable Annealed Importance Sampling Minimizes The Symmetrized Kullback-Leibler Divergence Between Initial and Target Distribution
by: Zenn, Johannes, et al.
Published: (2024)
by: Zenn, Johannes, et al.
Published: (2024)
Score-Regularized Joint Sampling with Importance Weights for Flow Matching
by: Liu, Xinshuang, et al.
Published: (2025)
by: Liu, Xinshuang, et al.
Published: (2025)
Task-Adaptive Pretrained Language Models via Clustered-Importance Sampling
by: Grangier, David, et al.
Published: (2024)
by: Grangier, David, et al.
Published: (2024)
Variational Self-Supervised Contrastive Learning Using Beta Divergence
by: Yavuz, Mehmet Can, et al.
Published: (2023)
by: Yavuz, Mehmet Can, et al.
Published: (2023)
Quotient DAGs for Off-Policy Evaluation:Forward-Flow Importance Sampling and Exact Slate Propensities
by: Xie, Ziwen, et al.
Published: (2026)
by: Xie, Ziwen, et al.
Published: (2026)
GRASS: Gradient-based Adaptive Layer-wise Importance Sampling for Memory-efficient Large Language Model Fine-tuning
by: Tian, Kaiyuan, et al.
Published: (2026)
by: Tian, Kaiyuan, et al.
Published: (2026)
A New Forward Discriminant Analysis Framework Based On Pillai's Trace and ULDA
by: Wang, Siyu, et al.
Published: (2024)
by: Wang, Siyu, et al.
Published: (2024)
Adaptive Pre-training Data Detection for Large Language Models via Surprising Tokens
by: Zhang, Anqi, et al.
Published: (2024)
by: Zhang, Anqi, et al.
Published: (2024)
Scalable Forward-Forward Algorithm
by: Krutsylo, Andrii
Published: (2025)
by: Krutsylo, Andrii
Published: (2025)
Contrastive Continual Learning with Importance Sampling and Prototype-Instance Relation Distillation
by: Li, Jiyong, et al.
Published: (2024)
by: Li, Jiyong, et al.
Published: (2024)
Near-Optimal Sample Complexities of Divergence-based S-rectangular Distributionally Robust Reinforcement Learning
by: Li, Zhenghao, et al.
Published: (2025)
by: Li, Zhenghao, et al.
Published: (2025)
A hitchhiker's guide to Poisson gradient estimation
by: Ibrahim, Michael, et al.
Published: (2026)
by: Ibrahim, Michael, et al.
Published: (2026)
Ensemble-Based Annealed Importance Sampling
by: Chen, Haoxuan, et al.
Published: (2024)
by: Chen, Haoxuan, et al.
Published: (2024)
Leveraging Black-box Models to Assess Feature Importance in Unconditional Distribution
by: Zhou, Jing, et al.
Published: (2024)
by: Zhou, Jing, et al.
Published: (2024)
Improved Forward-Forward Contrastive Learning
by: R, Gananath
Published: (2024)
by: R, Gananath
Published: (2024)
AutoDFP: Automatic Data-Free Pruning via Channel Similarity Reconstruction
by: Li, Siqi, et al.
Published: (2024)
by: Li, Siqi, et al.
Published: (2024)
Device Image-IV Mapping using Variational Autoencoder for Inverse Design and Forward Prediction
by: Lu, Thomas, et al.
Published: (2023)
by: Lu, Thomas, et al.
Published: (2023)
Feature Likelihood Divergence: Evaluating the Generalization of Generative Models Using Samples
by: Jiralerspong, Marco, et al.
Published: (2023)
by: Jiralerspong, Marco, et al.
Published: (2023)
Mirage or Method? How Model-Task Alignment Induces Divergent RL Conclusions
by: Wu, Haoze, et al.
Published: (2025)
by: Wu, Haoze, et al.
Published: (2025)
FLOPS: Forward Learning with OPtimal Sampling
by: Ren, Tao, et al.
Published: (2024)
by: Ren, Tao, et al.
Published: (2024)
Learning with Importance Weighted Variational Inference
by: Daudel, Kamélia, et al.
Published: (2024)
by: Daudel, Kamélia, et al.
Published: (2024)
Scalable and Efficient Temporal Graph Representation Learning via Forward Recent Sampling
by: Luo, Yuhong, et al.
Published: (2024)
by: Luo, Yuhong, et al.
Published: (2024)
Stabilizing Off-Policy Training for Long-Horizon LLM Agent via Turn-Level Importance Sampling and Clipping-Triggered Normalization
by: Li, Chenliang, et al.
Published: (2025)
by: Li, Chenliang, et al.
Published: (2025)
Similar Items
-
A Differentiable Partially Observable Generalized Linear Model with Forward-Backward Message Passing
by: Li, Chengrui, et al.
Published: (2024) -
Exploring Behavior-Relevant and Disentangled Neural Dynamics with Generative Diffusion Models
by: Wang, Yule, et al.
Published: (2024) -
Learning Time-Varying Multi-Region Brain Communications via Scalable Markovian Gaussian Processes
by: Li, Weihan, et al.
Published: (2024) -
Multi-Region Markovian Gaussian Process: An Efficient Method to Discover Directional Communications Across Multiple Brain Regions
by: Li, Weihan, et al.
Published: (2024) -
Uncovering Semantic Selectivity of Latent Groups in Higher Visual Cortex with Mutual Information-Guided Diffusion
by: Wang, Yule, et al.
Published: (2025)