25 citations · 87 across the 15 of their papers we have counts for
6 papers · 1 filter
Modeling Time-Series and Spatial Data for Recommendations and Other Applications
Vinayak Gupta
With the research directions described in this thesis, we seek to address the critical challenges in designing recommender systems that can understand the dynamics of continuous-ti…
Modeling Spatial Trajectories using Coarse-Grained Smartphone Logs
Vinayak Gupta, Srikanta Bedathur
Current approaches for points-of-interest (POI) recommendation learn the preferences of a user via the standard spatial features such as the POI coordinates, the social network, et…
Modeling Continuous Time Sequences with Intermittent Observations using Marked Temporal Point Processes
Vinayak Gupta, Srikanta Bedathur, Sourangshu Bhattacharya +1
A large fraction of data generated via human activities such as online purchases, health records, spatial mobility etc. can be represented as a sequence of events over a continuous…
ProActive: Self-Attentive Temporal Point Process Flows for Activity Sequences
Vinayak Gupta, Srikanta Bedathur
Any human activity can be represented as a temporal sequence of actions performed to achieve a certain goal. Unlike machine-made time series, these action sequences are highly disp…
Learning Temporal Point Processes for Efficient Retrieval of Continuous Time Event Sequences
Vinayak Gupta, Srikanta Bedathur, Abir De
Recent developments in predictive modeling using marked temporal point processes (MTPP) have enabled an accurate characterization of several real-world applications involving conti…
Doing More with Less: Overcoming Data Scarcity for POI Recommendation via Cross-Region Transfer
Vinayak Gupta, Srikanta Bedathur
Variability in social app usage across regions results in a high skew of the quantity and the quality of check-in data collected, which in turn is a challenge for effective locatio…