Vijaya Krishna Yalavarthi

According to our database, Vijaya Krishna Yalavarthi authored at least 18 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Marginalization Consistent Mixture of Separable Flows for Probabilistic Irregular Time Series Forecasting.

Vijaya Krishna Yalavarthi, Randolf Scholz, Kiran Madhusudhanan, Stefan Born, Lars Schmidt-Thieme

CoRR, 2024

Are EEG Sequences Time Series? EEG Classification with Time Series Models and Joint Subject Training.

Johannes Burchert, Thorben Werner, Vijaya Krishna Yalavarthi, Diego Coello de Portugal, Maximilian Stubbemann, Lars Schmidt-Thieme

CoRR, 2024

Probabilistic Forecasting of Irregular Time Series via Conditional Flows.

Vijaya Krishna Yalavarthi, Randolf Scholz, Stefan Born, Lars Schmidt-Thieme

CoRR, 2024

Functional Latent Dynamics for Irregularly Sampled Time Series Forecasting.

Christian Klötergens, Vijaya Krishna Yalavarthi, Maximilian Stubbemann, Lars Schmidt-Thieme

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

GraFITi: Graphs for Forecasting Irregularly Sampled Time Series.

Vijaya Krishna Yalavarthi, Kiran Madhusudhanan, Randolf Scholz, Nourhan Ahmed, Johannes Burchert, Shayan Jawed, Stefan Born, Lars Schmidt-Thieme

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Forecasting Irregularly Sampled Time Series using Graphs.

Vijaya Krishna Yalavarthi, Kiran Madusudanan, Randolf Scholz, Nourhan Ahmed, Johannes Burchert, Shayan Jawed, Stefan Born, Lars Schmidt-Thieme

CoRR, 2023

Forecasting Early with Meta Learning.

Shayan Jawed, Kiran Madhusudhanan, Vijaya Krishna Yalavarthi, Lars Schmidt-Thieme

Proceedings of the International Joint Conference on Neural Networks, 2023

Tripletformer for Probabilistic Interpolation of Irregularly sampled Time Series.

Vijaya Krishna Yalavarthi, Johannes Burchert, Lars Schmidt-Thieme

Proceedings of the IEEE International Conference on Big Data, 2023

2022

Tripletformer for Probabilistic Interpolation of Asynchronous Time Series.

Vijaya Krishna Yalavarthi, Johannes Burchert, Lars Schmidt-Thieme

CoRR, 2022

Open Set Recognition for Time Series Classification.

Tolga Akar, Thorben Werner, Vijaya Krishna Yalavarthi, Lars Schmidt-Thieme

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

DCSF: Deep Convolutional Set Functions for Classification of Asynchronous Time Series.

Vijaya Krishna Yalavarthi, Johannes Burchert, Lars Schmidt-Thieme

Proceedings of the 9th IEEE International Conference on Data Science and Advanced Analytics, 2022

2019

Gait Verification using Deep Learning with a Pairwise Loss.

Vijaya Krishna Yalavarthi, Josif Grabocka, Hareesh Mandalapu, Lars Schmidt-Thieme

Proceedings of the 2019 International Conference of the Biometrics Special Interest Group, 2019

2018

A Demonstration of PERC: Probabilistic Entity Resolution With Crowd Errors.

Xiangyu Ke, Michelle Teo, Arijit Khan, Vijaya Krishna Yalavarthi

Proc. VLDB Endow., 2018

Fast Influence Maximization in Dynamic Graphs: A Local Updating Approach.

Vijaya Krishna Yalavarthi, Arijit Khan

CoRR, 2018

Steering Top-k Influencers in Dynamic Graphs via Local Updates.

Vijaya Krishna Yalavarthi, Arijit Khan

Proceedings of the IEEE International Conference on Big Data (IEEE BigData 2018), 2018

2017

Probabilistic Entity Resolution with Imperfect Crowd.

Vijaya Krishna Yalavarthi, Xiangyu Ke, Arijit Khan

CoRR, 2017

Select Your Questions Wisely: For Entity Resolution With Crowd Errors.

Vijaya Krishna Yalavarthi, Xiangyu Ke, Arijit Khan

Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017

2016

A Novel Incremental Class Learning Technique for Multi-class Classification.

Meng Joo Er, Vijaya Krishna Yalavarthi, Ning Wang, Rajasekar Venkatesan

Proceedings of the Advances in Neural Networks - ISNN 2016, 2016