Search Results for author: Vinayak Gupta

Found 8 papers, 2 papers with code

Modeling Spatial Trajectories using Coarse-Grained Smartphone Logs

no code implementations29 Aug 2022 Vinayak Gupta, Srikanta Bedathur

In this paper, we present REVAMP, a sequential POI recommendation approach that utilizes the user activity on smartphone applications (or apps) to identify their mobility preferences.

Modeling Continuous Time Sequences with Intermittent Observations using Marked Temporal Point Processes

1 code implementation23 Jun 2022 Vinayak Gupta, Srikanta Bedathur, Sourangshu Bhattacharya, Abir De

In this work, we provide a novel unsupervised model and inference method for learning MTPP in presence of event sequences with missing events.

Point Processes Variational Inference

ProActive: Self-Attentive Temporal Point Process Flows for Activity Sequences

no code implementations10 Jun 2022 Vinayak Gupta, Srikanta Bedathur

In this paper, we present ProActive, a neural marked temporal point process (MTPP) framework for modeling the continuous-time distribution of actions in an activity sequence while simultaneously addressing three high-impact problems -- next action prediction, sequence-goal prediction, and end-to-end sequence generation.

Activity Recognition Time Series

Learning Temporal Point Processes for Efficient Retrieval of Continuous Time Event Sequences

1 code implementation17 Feb 2022 Vinayak Gupta, Srikanta Bedathur, Abir De

To tackle this, we propose NEUROSEQRET which learns to retrieve and rank a relevant set of continuous-time event sequences for a given query sequence, from a large corpus of sequences.

Point Processes

Doing More with Less: Overcoming Data Scarcity for POI Recommendation via Cross-Region Transfer

no code implementations16 Jan 2022 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 location recommender systems.

Graph Attention Meta-Learning +2

Learning Neural Models for Continuous-Time Sequences

no code implementations13 Nov 2021 Vinayak Gupta

The large volumes of data generated by human activities such as online purchases, health records, spatial mobility etc.

Point Processes

Region Invariant Normalizing Flows for Mobility Transfer

no code implementations13 Sep 2021 Vinayak Gupta, Srikanta Bedathur

Later, we transfer the model parameters of spatial and temporal flows trained on a data-rich origin region for the next check-in and time prediction in a target region with scarce checkin data.

Recommendation Systems Transfer Learning

BERT Meets Relational DB: Contextual Representations of Relational Databases

no code implementations30 Apr 2021 Siddhant Arora, Vinayak Gupta, Garima Gaur, Srikanta Bedathur

In this paper, we address the problem of learning low dimension representation of entities on relational databases consisting of multiple tables.

Representation Learning

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