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20162021
most citedTime2Vec: Learning a Vector Representation of Time

51 citations · 95 across the 11 of their papers we have counts for

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7 papers · 1 filter

cs.LG2021

Continuous Latent Process Flows

Ruizhi Deng, Marcus A. Brubaker, Greg Mori +1

Partial observations of continuous time-series dynamics at arbitrary time stamps exist in many disciplines. Fitting this type of data using statistical models with continuous dynam…

cs.LG20203 cited

Variational Hyper RNN for Sequence Modeling

Ruizhi Deng, Yanshuai Cao, Bo Chang +3

In this work, we propose a novel probabilistic sequence model that excels at capturing high variability in time series data, both across sequences and within an individual sequence…

cs.LG20193 cited

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…

cs.LG2019

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…

cs.LG201951 cited

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…

cs.LG2019

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…