← Authors

Alex Dimakis

33 papers · 2015–2025 · 7 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (11) 🧭 Keyword Pioneer 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (10) 🐝 Cross-Pollinator (11) 🌈 Renaissance Researcher (6) 🧬 Topic Evolution πŸ‘‘ Triple Crown πŸ‘₯ Mega-Team (34) πŸ† Keyword Champion (3) 🀝 Dynamic Duo (11) πŸ—ƒοΈ Keyword Collector (142) ⚑ Prolific Year (6) πŸ”₯ Unstoppable (9) πŸ“ˆ Trend Setter πŸ’Ž Century Club (33)

Conferences

ICML (15) NIPS (7) ICLR (4) AISTATS (3) ECCV (2) CVPR (1) EMNLP (1)

Top co-authors

Giannis Daras (11) Sujay Sanghavi (4) Ajil Jalal (3) Qi Lei (3) Yuval Dagan (3) Constantine Caramanis (3) Mi Luo (3) Negin Raoof (3) Kristen Grauman (3) Sanjay Shakkottai (3)

Keywords

generative model (6) compressed sensing (5) diffusion model (4) inverse problem (4) posterior sampling (4) generative modeling (2) image restoration (2) normalizing flow (2) neural network (2) representation learning (2) image denoising (2) distributed learning (2) image generation (2) zero-shot learning (1) stochastic gradient descent (1) contrastive learning (1) causal inference (1) wasserstein distance (1) principal component analysis (1) langevin dynamics (1)

Papers

Geometric Median (GM) Matching for Robust k-Subset Selection from Noisy Data ICML 2025
Viewpoint Rosetta Stone: Unlocking Unpaired Ego-Exo Videos for View-invariant Representation Learning CVPR 2025
Large Language Models as Realistic Microservice Trace Generators EMNLP 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
Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models Trained on Corrupted Data ICLR 2025
4Diff: 3D-Aware Diffusion Model for Third-to-First Viewpoint Translation ECCV 2024
SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors NIPS 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
Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Models NIPS 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
Ambient Diffusion: Learning Clean Distributions from Corrupted Data NIPS 2023
DataComp: In search of the next generation of multimodal datasets NIPS 2023
Consistent Diffusion Models: Mitigating Sampling Drift by Learning to be Consistent NIPS 2023
Score-Guided Intermediate Level Optimization: Fast Langevin Mixing for Inverse Problems ICML 2022
Multitasking Models are Robust to Structural Failure: A Neural Model for Bilingual Cognitive Reserve NIPS 2022
Zonotope Domains for Lagrangian Neural Network Verification NIPS 2022
Solving Inverse Problems with a Flow-based Noise Model ICML 2021
Intermediate Layer Optimization for Inverse Problems using Deep Generative Models ICML 2021
Fairness for Image Generation with Uncertain Sensitive Attributes ICML 2021
Instance-Optimal Compressed Sensing via Posterior Sampling ICML 2021
Provable Lipschitz Certification for Generative Models ICML 2021
Composing Normalizing Flows for Inverse Problems ICML 2021
SGD Learns One-Layer Networks in WGANs ICML 2020
Communication-Efficient Asynchronous Stochastic Frank-Wolfe over Nuclear-norm Balls AISTATS 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