Omri Azencot
12 papers · 2020–2025 · 5 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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🗺️ Taxonomy Completionist (25) 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Sprint 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird
🏆
Grand Slam
🏆
Keyword Champion
(2)
👑
Triple Crown
🗃️
Keyword Collector
(66)
📈
Trend Setter
💎
Century Club · Bronze
Top co-authors
Research topics
Machine Learning
(12)
Deep Learning
(10)
Core Methods
(7)
Optimization & Theory
(5)
Architectures
(4)
Learning Types · Machine Learning
(4)
Learning Types · Deep Learning
(4)
Models
(3)
Techniques
(2)
Artificial Intelligence
(1)
Computer Vision
(1)
Data Science & Analytics
(1)
Analysis
(1)
Core AI
(1)
Methods
(1)
Keywords
representation learning
(3)
sequential disentanglement
(2)
koopman theory
(2)
time series forecasting
(2)
generative model
(2)
self-supervised learning
(1)
model robustness
(1)
multi-task learning
(1)
regression
(1)
time series generation
(1)
time series
(1)
intrinsic dimension
(1)
eigenvalue decomposition
(1)
sentiment analysis
(1)
manifold sampling
(1)
neural network analysis
(1)
correlation clustering
(1)
nonlinear dynamics
(1)
generalization
(1)
variational framework
(1)
Papers
A Multi-Task Learning Approach to Linear Multivariate Forecasting
AISTATS 2025
Curvature Enhanced Data Augmentation for Regression
ICML 2025
First-Order Manifold Data Augmentation for Regression Learning
ICML 2024
Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEs
ICLR 2024
Sequential Disentanglement by Extracting Static Information From A Single Sequence Element
ICML 2024
Utilizing Image Transforms and Diffusion Models for Generative Modeling of Short and Long Time Series
NeurIPS 2024
An Operator Theoretic Approach for Analyzing Sequence Neural Networks
AAAI 2023
Data Representations’ Study of Latent Image Manifolds
ICML 2023
Multifactor Sequential Disentanglement via Structured Koopman Autoencoders
ICLR 2023
Sample and Predict Your Latent: Modality-free Sequential Disentanglement via Contrastive Estimation
ICML 2023
Lipschitz Recurrent Neural Networks
ICLR 2021
Forecasting Sequential Data Using Consistent Koopman Autoencoders
ICML 2020