Alex Dimakis

Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models Trained on Corrupted Data ICLR 2025 Geometric Median (GM) Matching for Robust k-Subset Selection from Noisy Data ICML 2025 Infilling Score: A Pretraining Data Detection Algorithm for Large Language Models ICLR 2025 Language models scale reliably with over-training and on downstream tasks ICLR 2025 Large Language Models as Realistic Microservice Trace Generators EMNLP 2025 Viewpoint Rosetta Stone: Unlocking Unpaired Ego-Exo Videos for View-invariant Representation Learning CVPR 2025 4Diff: 3D-Aware Diffusion Model for Third-to-First Viewpoint Translation ECCV 2024 Consistent Diffusion Meets Tweedie: Training Exact Ambient Diffusion Models with Noisy Data ICML 2024 Put Myself in Your Shoes: Lifting the Egocentric Perspective from Exocentric Videos ECCV 2024 SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors NeurIPS 2024 Ambient Diffusion: Learning Clean Distributions from Corrupted Data NeurIPS 2023 Consistent Diffusion Models: Mitigating Sampling Drift by Learning to be Consistent NeurIPS 2023 DataComp: In search of the next generation of multimodal datasets NeurIPS 2023 HotProtein: A Novel Framework for Protein Thermostability Prediction and Editing ICLR 2023 Restoration-Degradation Beyond Linear Diffusions: A Non-Asymptotic Analysis For DDIM-type Samplers ICML 2023 Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Models NeurIPS 2023 Multitasking Models are Robust to Structural Failure: A Neural Model for Bilingual Cognitive Reserve NeurIPS 2022 Score-Guided Intermediate Level Optimization: Fast Langevin Mixing for Inverse Problems ICML 2022 Zonotope Domains for Lagrangian Neural Network Verification NeurIPS 2022 Composing Normalizing Flows for Inverse Problems ICML 2021 Fairness for Image Generation with Uncertain Sensitive Attributes ICML 2021 Instance-Optimal Compressed Sensing via Posterior Sampling ICML 2021 Intermediate Layer Optimization for Inverse Problems using Deep Generative Models ICML 2021 Provable Lipschitz Certification for Generative Models ICML 2021 Solving Inverse Problems with a Flow-based Noise Model ICML 2021 Communication-Efficient Asynchronous Stochastic Frank-Wolfe over Nuclear-norm Balls AISTATS 2020 SGD Learns One-Layer Networks in WGANs ICML 2020 Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling ICML 2019 Gradient Coding from Cyclic MDS Codes and Expander Graphs ICML 2018 Contextual Bandits with Latent Confounders: An NMF Approach AISTATS 2017 Cost-Optimal Learning of Causal Graphs ICML 2017 Scalable Greedy Feature Selection via Weak Submodularity AISTATS 2017 Stay on path: PCA along graph paths ICML 2015