most citedLong Horizon Forecasting With Temporal Point Processes

9 citations · 16 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2021★ 9 cited

Long Horizon Forecasting With Temporal Point Processes

Prathamesh Deshpande, Kamlesh Marathe, Abir De +1

In recent years, marked temporal point processes (MTPPs) have emerged as a powerful modeling machinery to characterize asynchronous events in a wide variety of applications. MTPPs…

cs.LG2019★ 7 cited

Streaming Adaptation of Deep Forecasting Models using Adaptive Recurrent Units

Prathamesh Deshpande, Sunita Sarawagi

We present ARU, an Adaptive Recurrent Unit for streaming adaptation of deep globally trained time-series forecasting models. The ARU combines the advantages of learning complex dat…