51 citations · 98 across the 17 of their papers we have counts for
9 papers · 1 filter
Point Process Flows
Nazanin Mehrasa, Ruizhi Deng, Mohamed Osama Ahmed +5
Event sequences can be modeled by temporal point processes (TPPs) to capture their asynchronous and probabilistic nature. We propose an intensity-free framework that directly model…
Parity Partition Coding for Sharp Multi-Label Classification
Christopher G. Blake, Giuseppe Castiglione, Christopher Srinivasa +1
The problem of efficiently training and evaluating image classifiers that can distinguish between a large number of object categories is considered. A novel metric, sharpness, is p…
Noise Flow: Noise Modeling with Conditional Normalizing Flows
Abdelrahman Abdelhamed, Marcus A. Brubaker, Michael S. Brown
Modeling and synthesizing image noise is an important aspect in many computer vision applications. The long-standing additive white Gaussian and heteroscedastic (signal-dependent)…
Normalizing Flows: An Introduction and Review of Current Methods
Ivan Kobyzev, Simon J. D. Prince, Marcus A. Brubaker
Normalizing Flows are generative models which produce tractable distributions where both sampling and density evaluation can be efficient and exact. The goal of this survey article…
Time2Vec: Learning a Vector Representation of Time
Seyed Mehran Kazemi, Rishab Goel, Sepehr Eghbali +7
Time is an important feature in many applications involving events that occur synchronously and/or asynchronously. To effectively consume time information, recent studies have focu…
Diachronic Embedding for Temporal Knowledge Graph Completion
Rishab Goel, Seyed Mehran Kazemi, Marcus Brubaker +1
Knowledge graphs (KGs) typically contain temporal facts indicating relationships among entities at different times. Due to their incompleteness, several approaches have been propos…