Maximilian Nickel

86 papers A* 22A 1B 2Misc 1Journal 41Unranked 15

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Cultivating Pluralism In Algorithmic Monoculture: The Community Alignment Dataset. CoRR Lily Hong Zhang, Smitha Milli, Karen Jusko, Jonathan Smith, Brandon Amos, Wassim Bouaziz, Manon Revel, Jack Kussman, Lisa Titus, Bhaktipriya Radharapu, Jane Yu, Vidya Sarma, Kris Rose, Maximilian Nickel
2025	J	`jnl`	LLM Output Homogenization is Task Dependent. CoRR Shomik Jain, Jack Lanchantin, Maximilian Nickel, Karen Ullrich, Ashia Wilson, Jamelle Watson-Daniels
2025	A*	`conf`	Representative Ranking for Deliberation in the Public Sphere. ICML Manon Revel, Smitha Milli, Tyler Lu, Jamelle Watson-Daniels, Maximilian Nickel
2025	J	`jnl`	Representative Ranking for Deliberation in the Public Sphere. CoRR Manon Revel, Smitha Milli, Tyler Lu, Jamelle Watson-Daniels, Maximilian Nickel
2024	Misc	`conf`	Assessing Neural Network Representations During Training Using Noise-Resilient Diffusion Spectral Entropy. CISS Danqi Liao, Chen Liu, Benjamin W. Christensen, Alexander Tong, Guillaume Huguet, Guy Wolf, Maximilian Nickel, Ian Adelstein, Smita Krishnaswamy
2024	A*	`conf`	Generalized Schrödinger Bridge Matching. ICLR Guan-Horng Liu, Yaron Lipman, Maximilian Nickel, Brian Karrer, Evangelos A. Theodorou, Ricky T. Q. Chen
2024	A*	`conf`	No Free Delivery Service: Epistemic limits of passive data collection in complex social systems. NeurIPS Maximilian Nickel
2024	J	`jnl`	No Free Delivery Service: Epistemic limits of passive data collection in complex social systems. CoRR Maximilian Nickel
2024	J	`jnl`	Sense and Sensitivity: Evaluating the simulation of social dynamics via Large Language Models. CoRR Da Ju, Adina Williams, Brian Karrer, Maximilian Nickel
2024	—	`conf`	System-2 Recommenders: Disentangling Utility and Engagement in Recommendation Systems via Temporal Point-Processes. FAccT Arpit Agarwal, Nicolas Usunier, Alessandro Lazaric, Maximilian Nickel
2024	J	`jnl`	System-2 Recommenders: Disentangling Utility and Engagement in Recommendation Systems via Temporal Point-Processes. CoRR Arpit Agarwal, Nicolas Usunier, Alessandro Lazaric, Maximilian Nickel
2023	J	`jnl`	Assessing Neural Network Representations During Training Using Noise-Resilient Diffusion Spectral Entropy. CoRR Danqi Liao, Chen Liu, Benjamin W. Christensen, Alexander Tong, Guillaume Huguet, Guy Wolf, Maximilian Nickel, Ian Adelstein, Smita Krishnaswamy
2023	A*	`conf`	Flow Matching for Generative Modeling. ICLR Yaron Lipman, Ricky T. Q. Chen, Heli Ben-Hamu, Maximilian Nickel, Matthew Le
2023	J	`jnl`	Generalized Schrödinger Bridge Matching. CoRR Guan-Horng Liu, Yaron Lipman, Maximilian Nickel, Brian Karrer, Evangelos A. Theodorou, Ricky T. Q. Chen
2023	J	`jnl`	Graph topological property recovery with heat and wave dynamics-based features on graphs. CoRR Dhananjay Bhaskar, Yanlei Zhang, Charles Xu, Xingzhi Sun, Oluwadamilola Fasina, Guy Wolf, Maximilian Nickel, Michael Perlmutter, Smita Krishnaswamy
2023	—	`conf`	Group fairness without demographics using social networks. FAccT David Liu, Virginie Do, Nicolas Usunier, Maximilian Nickel
2023	J	`jnl`	Group fairness without demographics using social networks. CoRR David Liu, Virginie Do, Nicolas Usunier, Maximilian Nickel
2023	J	`jnl`	Hyperbolic Image-Text Representations. CoRR Karan Desai, Maximilian Nickel, Tanmay Rajpurohit, Justin Johnson, Ramakrishna Vedantam
2023	A*	`conf`	Hyperbolic Image-text Representations. ICML Karan Desai, Maximilian Nickel, Tanmay Rajpurohit, Justin Johnson, Shanmukha Ramakrishna Vedantam
2023	J	`jnl`	Neural FIM for learning Fisher Information Metrics from point cloud data. CoRR Oluwadamilola Fasina, Guillaume Huguet, Alexander Tong, Yanlei Zhang, Guy Wolf, Maximilian Nickel, Ian Adelstein, Smita Krishnaswamy
2023	A*	`conf`	Neural FIM for learning Fisher information metrics from point cloud data. ICML Oluwadamilola Fasina, Guillaume Huguet, Alexander Tong, Yanlei Zhang, Guy Wolf, Maximilian Nickel, Ian Adelstein, Smita Krishnaswamy
2023	A*	`conf`	On Kinetic Optimal Probability Paths for Generative Models. ICML Neta Shaul, Ricky T. Q. Chen, Maximilian Nickel, Matthew Le, Yaron Lipman
2023	J	`jnl`	On Kinetic Optimal Probability Paths for Generative Models. CoRR Neta Shaul, Ricky T. Q. Chen, Maximilian Nickel, Matt Le, Yaron Lipman
2023	J	`jnl`	Weisfeiler and Lehman Go Measurement Modeling: Probing the Validity of the WL Test. CoRR Arjun Subramonian, Adina Williams, Maximilian Nickel, Yizhou Sun, Levent Sagun
2022	A	`conf`	Can I see an Example? Active Learning the Long Tail of Attributes and Relations. BMVC Tyler L. Hayes, Maximilian Nickel, Christopher Kanan, Ludovic Denoyer, Arthur Szlam
2022	J	`jnl`	Can I see an Example? Active Learning the Long Tail of Attributes and Relations. CoRR Tyler L. Hayes, Maximilian Nickel, Christopher Kanan, Ludovic Denoyer, Arthur Szlam
2022	J	`jnl`	Flow Matching for Generative Modeling. CoRR Yaron Lipman, Ricky T. Q. Chen, Heli Ben-Hamu, Maximilian Nickel, Matt Le
2022	J	`jnl`	Latent Discretization for Continuous-time Sequence Compression. CoRR Ricky T. Q. Chen, Matthew Le, Matthew J. Muckley, Maximilian Nickel, Karen Ullrich
2022	A*	`conf`	Matching Normalizing Flows and Probability Paths on Manifolds. ICML Heli Ben-Hamu, Samuel Cohen, Joey Bose, Brandon Amos, Maximilian Nickel, Aditya Grover, Ricky T. Q. Chen, Yaron Lipman
2022	J	`jnl`	Matching Normalizing Flows and Probability Paths on Manifolds. CoRR Heli Ben-Hamu, Samuel Cohen, Joey Bose, Brandon Amos, Aditya Grover, Maximilian Nickel, Ricky T. Q. Chen, Yaron Lipman
2022	A*	`conf`	Semi-Discrete Normalizing Flows through Differentiable Tessellation. NeurIPS Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel
2022	J	`jnl`	Semi-Discrete Normalizing Flows through Differentiable Tessellation. CoRR Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel
2021	A*	`conf`	CURI: A Benchmark for Productive Concept Learning Under Uncertainty. ICML Ramakrishna Vedantam, Arthur Szlam, Maximilian Nickel, Ari Morcos, Brenden M. Lake
2021	A*	`conf`	Learning Neural Event Functions for Ordinary Differential Equations. ICLR Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel
2021	A*	`conf`	Modeling Sparse Information Diffusion at Scale via Lazy Multivariate Hawkes Processes. WWW Maximilian Nickel, Matthew Le
2021	A*	`conf`	Moser Flow: Divergence-based Generative Modeling on Manifolds. NeurIPS Noam Rozen, Aditya Grover, Maximilian Nickel, Yaron Lipman
2021	J	`jnl`	Moser Flow: Divergence-based Generative Modeling on Manifolds. CoRR Noam Rozen, Aditya Grover, Maximilian Nickel, Yaron Lipman
2021	A*	`conf`	Neural Spatio-Temporal Point Processes. ICLR Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel
2020	J	`jnl`	CURI: A Benchmark for Productive Concept Learning Under Uncertainty. CoRR Ramakrishna Vedantam, Arthur Szlam, Maximilian Nickel, Ari Morcos, Brenden M. Lake
2020	J	`jnl`	Learning Multivariate Hawkes Processes at Scale. CoRR Maximilian Nickel, Matthew Le
2020	J	`jnl`	Learning Neural Event Functions for Ordinary Differential Equations. CoRR Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel
2020	J	`jnl`	Neural Spatio-Temporal Point Processes. CoRR Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel
2020	A*	`conf`	Riemannian Continuous Normalizing Flows. NeurIPS Emile Mathieu, Maximilian Nickel
2020	J	`jnl`	Riemannian Continuous Normalizing Flows. CoRR Emile Mathieu, Maximilian Nickel
2019	A*	`conf`	Hyperbolic Graph Neural Networks. NeurIPS Qi Liu, Maximilian Nickel, Douwe Kiela
2019	J	`jnl`	Hyperbolic Graph Neural Networks. CoRR Qi Liu, Maximilian Nickel, Douwe Kiela
2019	—	`conf`	Inferring Concept Hierarchies from Text Corpora via Hyperbolic Embeddings. ACL (1) Matt Le, Stephen Roller, Laetitia Papaxanthos, Douwe Kiela, Maximilian Nickel
2019	J	`jnl`	Inferring Concept Hierarchies from Text Corpora via Hyperbolic Embeddings. CoRR Matt Le, Stephen Roller, Laetitia Papaxanthos, Douwe Kiela, Maximilian Nickel
2019	—	`conf`	Revisiting the Evaluation of Theory of Mind through Question Answering. EMNLP/IJCNLP (1) Matthew Le, Y-Lan Boureau, Maximilian Nickel
2019	A*	`conf`	Task-Driven Modular Networks for Zero-Shot Compositional Learning. ICCV Senthil Purushwalkam, Maximilian Nickel, Abhinav Gupta, Marc'Aurelio Ranzato
2019	J	`jnl`	Task-Driven Modular Networks for Zero-Shot Compositional Learning. CoRR Senthil Purushwalkam, Maximilian Nickel, Abhinav Gupta, Marc'Aurelio Ranzato
2018	—	`conf`	Hearst Patterns Revisited: Automatic Hypernym Detection from Large Text Corpora. ACL (2) Stephen Roller, Douwe Kiela, Maximilian Nickel
2018	J	`jnl`	Hearst Patterns Revisited: Automatic Hypernym Detection from Large Text Corpora. CoRR Stephen Roller, Douwe Kiela, Maximilian Nickel
2018	A*	`conf`	Learning Continuous Hierarchies in the Lorentz Model of Hyperbolic Geometry. ICML Maximilian Nickel, Douwe Kiela
2018	J	`jnl`	Learning Continuous Hierarchies in the Lorentz Model of Hyperbolic Geometry. CoRR Maximilian Nickel, Douwe Kiela
2018	—	`conf`	Learning Visually Grounded Sentence Representations. NAACL-HLT Douwe Kiela, Alexis Conneau, Allan Jabri, Maximilian Nickel
2018	—	`ch.`	Relational Models. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. Volker Tresp, Maximilian Nickel
2018	A*	`conf`	Separating Self-Expression and Visual Content in Hashtag Supervision. CVPR Andreas Veit, Maximilian Nickel, Serge J. Belongie, Laurens van der Maaten
2017	J	`jnl`	Complex and Holographic Embeddings of Knowledge Graphs: A Comparison. CoRR Théo Trouillon, Maximilian Nickel
2017	—	`conf`	Fast Linear Model for Knowledge Graph Embeddings. AKBC@NIPS Armand Joulin, Edouard Grave, Piotr Bojanowski, Maximilian Nickel, Tomás Mikolov
2017	J	`jnl`	Fast Linear Model for Knowledge Graph Embeddings. CoRR Armand Joulin, Edouard Grave, Piotr Bojanowski, Maximilian Nickel, Tomás Mikolov
2017	J	`jnl`	Learning Visually Grounded Sentence Representations. CoRR Douwe Kiela, Alexis Conneau, Allan Jabri, Maximilian Nickel
2017	—	`conf`	Poincaré Embeddings for Learning Hierarchical Representations. NIPS Maximilian Nickel, Douwe Kiela
2017	J	`jnl`	Poincaré Embeddings for Learning Hierarchical Representations. CoRR Maximilian Nickel, Douwe Kiela
2017	J	`jnl`	Separating Self-Expression and Visual Content in Hashtag Supervision. CoRR Andreas Veit, Maximilian Nickel, Serge J. Belongie, Laurens van der Maaten
2016	J	`jnl`	A Review of Relational Machine Learning for Knowledge Graphs. Proc. IEEE Maximilian Nickel, Kevin Murphy, Volker Tresp, Evgeniy Gabrilovich
2016	A*	`conf`	Holographic Embeddings of Knowledge Graphs. AAAI Maximilian Nickel, Lorenzo Rosasco, Tomaso A. Poggio
2016	J	`jnl`	Relational Models. CoRR Volker Tresp, Maximilian Nickel
2015	J	`jnl`	A Review of Relational Machine Learning for Knowledge Graphs: From Multi-Relational Link Prediction to Automated Knowledge Graph Construction. CoRR Maximilian Nickel, Kevin Murphy, Volker Tresp, Evgeniy Gabrilovich
2015	J	`jnl`	Holographic Embeddings of Knowledge Graphs. CoRR Maximilian Nickel, Lorenzo Rosasco, Tomaso A. Poggio
2014	J	`jnl`	A scalable approach for statistical learning in semantic graphs. Semantic Web Yi Huang, Volker Tresp, Maximilian Nickel, Achim Rettinger, Hans-Peter Kriegel
2014	B	`conf`	Large-scale factorization of type-constrained multi-relational data. DSAA Denis Krompass, Maximilian Nickel, Volker Tresp
2014	—	`conf`	Probabilistic Latent-Factor Database Models. LD4KD Denis Krompass, Xueyan Jiang, Maximilian Nickel, Volker Tresp
2014	—	`conf`	Querying Factorized Probabilistic Triple Databases. ISWC (2) Denis Krompaß, Maximilian Nickel, Volker Tresp
2014	—	`ch.`	Querying the Web with Statistical Machine Learning. Towards the Internet of Services Volker Tresp, Yi Huang, Maximilian Nickel
2014	—	`conf`	Reducing the Rank in Relational Factorization Models by Including Observable Patterns. NIPS Maximilian Nickel, Xueyan Jiang, Volker Tresp
2014	—	`ch.`	Relational Models. Encyclopedia of Social Network Analysis and Mining Volker Tresp, Maximilian Nickel
2013	—	`conf`	An Analysis of Tensor Models for Learning on Structured Data. ECML/PKDD (2) Maximilian Nickel, Volker Tresp
2013	J	`jnl`	Logistic Tensor Factorization for Multi-Relational Data. CoRR Maximilian Nickel, Volker Tresp
2013	—	`conf`	Tensor Factorization for Multi-relational Learning. ECML/PKDD (3) Maximilian Nickel, Volker Tresp
2013	—	`—`	Tensor factorization for relational learning. Maximilian Nickel
2012	B	`conf`	Combining Information Extraction, Deductive Reasoning and Machine Learning for Relation Prediction. ESWC Xueyan Jiang, Yi Huang, Maximilian Nickel, Volker Tresp
2012	A*	`conf`	Factorizing YAGO: scalable machine learning for linked data. WWW Maximilian Nickel, Volker Tresp, Hans-Peter Kriegel
2012	—	`conf`	Link Prediction in Multi-relational Graphs using Additive Models. SeRSy Xueyan Jiang, Volker Tresp, Yi Huang, Maximilian Nickel
2012	—	`conf`	Scalable Relation Prediction Exploiting Both Intrarelational Correlation and Contextual Information. ECML/PKDD (1) Xueyan Jiang, Volker Tresp, Yi Huang, Maximilian Nickel, Hans-Peter Kriegel
2011	A*	`conf`	A Three-Way Model for Collective Learning on Multi-Relational Data. ICML Maximilian Nickel, Volker Tresp, Hans-Peter Kriegel