Nickel, Maximilian

22 publications

ICML 2025 Representative Ranking for Deliberation in the Public Sphere Manon Revel, Smitha Milli, Tyler Lu, Jamelle Watson-Daniels, Maximilian Nickel

ICMLW 2024 Collaborative Learning Under Strategic Behavior: Mechanisms for Eliciting Feedback in Principal-Agent Bandit Games Ramakrishnan K, Arpit Agarwal, Lakshminarayanan Subramanian, Maximilian Nickel

ICLR 2024 Generalized Schrödinger Bridge Matching Guan-Horng Liu, Yaron Lipman, Maximilian Nickel, Brian Karrer, Evangelos Theodorou, Ricky T. Q. Chen

NeurIPS 2024 No Free Delivery Service: Epistemic Limits of Passive Data Collection in Complex Social Systems Maximilian Nickel

ICLR 2023 Flow Matching for Generative Modeling Yaron Lipman, Ricky T. Q. Chen, Heli Ben-Hamu, Maximilian Nickel, Matthew Le

ICML 2023 Hyperbolic Image-Text Representations Karan Desai, Maximilian Nickel, Tanmay Rajpurohit, Justin Johnson, Shanmukha Ramakrishna Vedantam

ICLRW 2023 Hyperbolic Image-Text Representations Karan Desai, Maximilian Nickel, Tanmay Rajpurohit, Justin Johnson, Shanmukha Ramakrishna Vedantam

ICML 2023 Neural FIM for Learning Fisher Information Metrics from Point Cloud Data Oluwadamilola Fasina, Guillaume Huguet, Alexander Tong, Yanlei Zhang, Guy Wolf, Maximilian Nickel, Ian Adelstein, Smita Krishnaswamy

ICML 2023 On Kinetic Optimal Probability Paths for Generative Models Neta Shaul, Ricky T. Q. Chen, Maximilian Nickel, Matthew Le, Yaron Lipman

NeurIPS 2022 Semi-Discrete Normalizing Flows Through Differentiable Tessellation Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel

ICLRW 2022 Semi-Discrete Normalizing Flows Through Differentiable Voronoi Tessellation Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel

ICLR 2021 Learning Neural Event Functions for Ordinary Differential Equations Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel

NeurIPS 2021 Moser Flow: Divergence-Based Generative Modeling on Manifolds Noam Rozen, Aditya Grover, Maximilian Nickel, Yaron Lipman

ICLR 2021 Neural Spatio-Temporal Point Processes Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel

NeurIPS 2020 Riemannian Continuous Normalizing Flows Emile Mathieu, Maximilian Nickel

NeurIPS 2019 Hyperbolic Graph Neural Networks Qi Liu, Maximilian Nickel, Douwe Kiela

AAAI 2016 Holographic Embeddings of Knowledge Graphs Maximilian Nickel, Lorenzo Rosasco, Tomaso A. Poggio

NeurIPS 2014 Reducing the Rank in Relational Factorization Models by Including Observable Patterns Maximilian Nickel, Xueyan Jiang, Volker Tresp

ECML-PKDD 2013 An Analysis of Tensor Models for Learning on Structured Data Maximilian Nickel, Volker Tresp

ECML-PKDD 2013 Tensor Factorization for Multi-Relational Learning Maximilian Nickel, Volker Tresp

ECML-PKDD 2012 Scalable Relation Prediction Exploiting Both Intrarelational Correlation and Contextual Information Xueyan Jiang, Volker Tresp, Yi Huang, Maximilian Nickel, Hans-Peter Kriegel

ICML 2011 A Three-Way Model for Collective Learning on Multi-Relational Data Maximilian Nickel, Volker Tresp, Hans-Peter Kriegel