:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Brekelmans, Rob, Huang, Sicong, Ghassemi, Marzyeh, Steeg, Greg Ver, Grosse, Roger, Makhzani, Alireza
Natura:	Preprint
Pubblicazione:	2023
Soggetti:	Machine Learning
Accesso online:	https://arxiv.org/abs/2303.06992
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Probabilistic Inference in Language Models via Twisted Sequential Monte Carlo
di: Zhao, Stephen, et al.
Pubblicazione: (2024)

Measurement-Aligned Sampling for Inverse Problem
di: Zhang, Shaorong, et al.
Pubblicazione: (2025)

Annealed Importance Sampling with q-Paths
di: Brekelmans, Rob, et al.
Pubblicazione: (2020)

Generation Order and Parallel Decoding in Masked Diffusion Models: An Information-Theoretic Perspective
di: Zhang, Shaorong, et al.
Pubblicazione: (2026)

MMG: Mutual Information Estimation via the MMSE Gap in Diffusion
di: Yu, Longxuan, et al.
Pubblicazione: (2025)

Local MAP Sampling for Diffusion Models
di: Zhang, Shaorong, et al.
Pubblicazione: (2025)

Measuring Stochastic Data Complexity with Boltzmann Influence Functions
di: Ng, Nathan, et al.
Pubblicazione: (2024)

Discrete Stochastic Localization for Non-autoregressive Generation
di: Wu, Yunshu, et al.
Pubblicazione: (2026)

Discrete Stochastic Localization for Non-autoregressive Generation
di: Wu, Yunshu, et al.
Pubblicazione: (2026)

A Computational Framework for Solving Wasserstein Lagrangian Flows
di: Neklyudov, Kirill, et al.
Pubblicazione: (2023)

Variational Representations of Annealing Paths: Bregman Information under Monotonic Embedding
di: Brekelmans, Rob, et al.
Pubblicazione: (2022)

Exploring the Design Space of Diffusion Bridge Models
di: Zhang, Shaorong, et al.
Pubblicazione: (2024)

Making Sense Of Distributed Representations With Activation Spectroscopy
di: Reing, Kyle, et al.
Pubblicazione: (2025)

Reducing the Probability of Undesirable Outputs in Language Models Using Probabilistic Inference
di: Zhao, Stephen, et al.
Pubblicazione: (2025)

Is Your Diffusion Sampler Actually Correct? A Sampler-Centric Evaluation of Discrete Diffusion Language Models
di: Tang, Luhan, et al.
Pubblicazione: (2026)

Learning Morphisms with Gauss-Newton Approximation for Growing Networks
di: Lawton, Neal, et al.
Pubblicazione: (2024)

Interpretable Diffusion via Information Decomposition
di: Kong, Xianghao, et al.
Pubblicazione: (2023)

Asymmetric Bias in Text-to-Image Generation with Adversarial Attacks
di: Shahgir, Haz Sameen, et al.
Pubblicazione: (2023)

Your Diffusion Model is Secretly a Noise Classifier and Benefits from Contrastive Training
di: Wu, Yunshu, et al.
Pubblicazione: (2024)

Random Cycle Coding: Lossless Compression of Cluster Assignments via Bits-Back Coding
di: Severo, Daniel, et al.
Pubblicazione: (2024)

Views Can Be Deceiving: Improved SSL Through Feature Space Augmentation
di: Hamidieh, Kimia, et al.
Pubblicazione: (2024)

Spectral Regularization for Diffusion Models
di: Chandran, Satish, et al.
Pubblicazione: (2026)

MaskMedPaint: Masked Medical Image Inpainting with Diffusion Models for Mitigation of Spurious Correlations
di: Jin, Qixuan, et al.
Pubblicazione: (2024)

FedDAPL: Toward Client-Private Generalization in Federated Learning
di: Loaliyan, Soroosh Safari, et al.
Pubblicazione: (2025)

AbFlowNet: Optimizing Antibody-Antigen Binding Energy via Diffusion-GFlowNet Fusion
di: Abir, Abrar Rahman, et al.
Pubblicazione: (2025)

What's in a Query: Polarity-Aware Distribution-Based Fair Ranking
di: Balagopalan, Aparna, et al.
Pubblicazione: (2025)

Interpretable Measures of Conceptual Similarity by Complexity-Constrained Descriptive Auto-Encoding
di: Achille, Alessandro, et al.
Pubblicazione: (2024)

Knowledge Enhanced Multi-Domain Recommendations in an AI Assistant Application
di: Markowitz, Elan, et al.
Pubblicazione: (2023)

Prompt Perturbation Consistency Learning for Robust Language Models
di: Qiang, Yao, et al.
Pubblicazione: (2024)

Data Debiasing with Datamodels (D3M): Improving Subgroup Robustness via Data Selection
di: Jain, Saachi, et al.
Pubblicazione: (2024)

Feynman-Kac Correctors in Diffusion: Annealing, Guidance, and Product of Experts
di: Skreta, Marta, et al.
Pubblicazione: (2025)

An Investigation of Memorization Risk in Healthcare Foundation Models
di: Tonekaboni, Sana, et al.
Pubblicazione: (2025)

Aggregation Hides Out-of-Distribution Generalization Failures from Spurious Correlations
di: Salaudeen, Olawale, et al.
Pubblicazione: (2025)

Robustness Beyond Known Groups with Low-rank Adaptation
di: Gourabathina, Abinitha, et al.
Pubblicazione: (2026)

DSL-LLaDA: Scaling Continuous Denoising to 8B Masked Diffusion LMs
di: Yu, Longxuan, et al.
Pubblicazione: (2026)

QuAILoRA: Quantization-Aware Initialization for LoRA
di: Lawton, Neal, et al.
Pubblicazione: (2024)

Event-Based Contrastive Learning for Medical Time Series
di: Jeong, Hyewon, et al.
Pubblicazione: (2023)

Improving Black-box Robustness with In-Context Rewriting
di: O'Brien, Kyle, et al.
Pubblicazione: (2024)

In the Name of Fairness: Assessing the Bias in Clinical Record De-identification
di: Xiao, Yuxin, et al.
Pubblicazione: (2023)

Speak Easy: Eliciting Harmful Jailbreaks from LLMs with Simple Interactions
di: Chan, Yik Siu, et al.
Pubblicazione: (2025)