Alexandros Kalousis

21 papers · 2011–2025 · 7 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 (42) 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Half 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird

🌱 Topic Pioneer 🔬 Deep Specialist (10) 🏆 Grand Slam 🏆 Keyword Champion 🧭 Keyword Pioneer 📈 Trend Setter 🚀 Conference Pioneer 🗃️ Keyword Collector (115) 🔥 Unstoppable · Bronze 💎 Century Club · Bronze 🌈 Renaissance Researcher (6)

Venues

NeurIPS (6) ICML (5) AISTATS (4) ACML (3) AAAI (1) ICLR (1) NAACL (1)

Top co-authors

Jun Wang (6) Naoya Takeishi (4) Amina Mollaysa (3) Ke Sun (3) Adam Woznica (3) Stephane Marchand-Maillet (3) Huyen Do (2) Lionel Blondé (2) Maciej Falkiewicz (2) Yoann Boget (2)

Research topics

Machine Learning (17) Core Methods (14) Deep Learning (10) Optimization & Theory (8) Learning Types · Machine Learning (5) Models (5) Artificial Intelligence (4) Learning Types · Deep Learning (4) Reinforcement Learning (3) Architectures (3) Core AI (3) Methods (3) Applications (2) Interdisciplinary (1) Knowledge & Reasoning (1)

Keywords

metric learning (5) distance metric (3) support vector machine (3) nearest neighbor (2) feature side-information (2) unsupervised learning (2) generative model (2) probability distribution (2) anchor point (2) imitation learning (2) generative adversarial network (2) neural network (2) bayesian inference (2) manifold regularization (1) feature learning (1) convex optimization (1) multi-source learning (1) multi-task learning (1) representation learning (1) optimal transport (1)

Papers

GLAD: Improving Latent Graph Generative Modeling with Simple Quantization AAAI 2025 MING: A Functional Approach to Learning Molecular Generative Models AISTATS 2025 Mimicking Better by Matching the Approximate Action Distribution ICML 2024 Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability NeurIPS 2023 Deep Grey-Box Modeling With Adaptive Data-Driven Models Toward Trustworthy Estimation of Theory-Driven Models AISTATS 2023 Graph annotation generative adversarial networks ACML 2022 Kanerva++: Extending the Kanerva Machine With Differentiable, Locally Block Allocated Latent Memory ICLR 2021 Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling NeurIPS 2021 Goal-directed Generation of Discrete Structures with Conditional Generative Models NeurIPS 2020 Learning to Augment with Feature Side-information ACML 2019 Sample-Efficient Imitation Learning via Generative Adversarial Nets AISTATS 2019 DeepAlignment: Unsupervised Ontology Matching with Refined Word Vectors NAACL 2018 Learning Predictive Leading Indicators for Forecasting Time Series Systems with Unknown Clusters of Forecast Tasks ACML 2017 Regularising Non-linear Models Using Feature Side-information ICML 2017 Information Geometry and Minimum Description Length Networks ICML 2015 Space-Time Local Embeddings NeurIPS 2015 Two-Stage Metric Learning ICML 2014 Convex formulations of radius-margin based Support Vector Machines ICML 2013 A metric learning perspective of SVM: on the relation of LMNN and SVM AISTATS 2012 Parametric Local Metric Learning for Nearest Neighbor Classification NeurIPS 2012 Metric Learning with Multiple Kernels NeurIPS 2011