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09/18/2023
Graph topological property recovery with heat and wave dynamics-based features on graphs
In this paper, we propose Graph Differential Equation Network (GDeNet), ...
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07/11/2023
Weisfeiler and Lehman Go Measurement Modeling: Probing the Validity of the WL Test
The expressive power of graph neural networks is usually measured by com...
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06/11/2023
On Kinetic Optimal Probability Paths for Generative Models
Recent successful generative models are trained by fitting a neural netw...
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05/19/2023
Group fairness without demographics using social networks
Group fairness is a popular approach to prevent unfavorable treatment of...
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04/18/2023
Hyperbolic Image-Text Representations
Visual and linguistic concepts naturally organize themselves in a hierar...
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12/28/2022
Latent Discretization for Continuous-time Sequence Compression
Neural compression offers a domain-agnostic approach to creating codecs ...
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10/06/2022
Flow Matching for Generative Modeling
We introduce a new paradigm for generative modeling built on Continuous ...
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07/11/2022
Matching Normalizing Flows and Probability Paths on Manifolds
Continuous Normalizing Flows (CNFs) are a class of generative models tha...
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03/14/2022
Semi-Discrete Normalizing Flows through Differentiable Tessellation
Mapping between discrete and continuous distributions is a difficult tas...
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03/11/2022
Can I see an Example? Active Learning the Long Tail of Attributes and Relations
There has been significant progress in creating machine learning models ...
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08/18/2021
Moser Flow: Divergence-based Generative Modeling on Manifolds
We are interested in learning generative models for complex geometries d...
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11/09/2020
Neural Spatio-Temporal Point Processes
We propose a new class of parameterizations for spatio-temporal point pr...
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11/08/2020
Learning Neural Event Functions for Ordinary Differential Equations
The existing Neural ODE formulation relies on an explicit knowledge of t...
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10/06/2020
CURI: A Benchmark for Productive Concept Learning Under Uncertainty
Humans can learn and reason under substantial uncertainty in a space of ...
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06/18/2020
Riemannian Continuous Normalizing Flows
Normalizing flows have shown great promise for modelling flexible probab...
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02/28/2020
Learning Multivariate Hawkes Processes at Scale
Multivariate Hawkes Processes (MHPs) are an important class of temporal ...
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10/28/2019
Hyperbolic Graph Neural Networks
Learning from graph-structured data is an important task in machine lear...
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05/15/2019
Task-Driven Modular Networks for Zero-Shot Compositional Learning
One of the hallmarks of human intelligence is the ability to compose lea...
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02/03/2019
Inferring Concept Hierarchies from Text Corpora via Hyperbolic Embeddings
We consider the task of inferring is-a relationships from large text cor...
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06/09/2018
Learning Continuous Hierarchies in the Lorentz Model of Hyperbolic Geometry
We are concerned with the discovery of hierarchical relationships from l...
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06/08/2018
Hearst Patterns Revisited: Automatic Hypernym Detection from Large Text Corpora
Methods for unsupervised hypernym detection may broadly be categorized a...
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11/27/2017
Separating Self-Expression and Visual Content in Hashtag Supervision
The variety, abundance, and structured nature of hashtags make them an i...
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10/30/2017
Fast Linear Model for Knowledge Graph Embeddings
This paper shows that a simple baseline based on a Bag-of-Words (BoW) re...
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07/19/2017
Learning Visually Grounded Sentence Representations
We introduce a variety of models, trained on a supervised image captioni...
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07/05/2017
Complex and Holographic Embeddings of Knowledge Graphs: A Comparison
Embeddings of knowledge graphs have received significant attention due t...
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05/22/2017
Poincaré Embeddings for Learning Hierarchical Representations
Representation learning has become an invaluable approach for learning f...
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09/11/2016
Relational Models
We provide a survey on relational models. Relational models describe com...
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10/16/2015
Holographic Embeddings of Knowledge Graphs
Learning embeddings of entities and relations is an efficient and versat...
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03/02/2015
A Review of Relational Machine Learning for Knowledge Graphs
Relational machine learning studies methods for the statistical analysis...
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06/10/2013
