research
∙
01/26/2023
Neural Dynamic Focused Topic Model
Topic models and all their variants analyse text by learning meaningful ...
share
research
∙
11/01/2022
The future is different: Large pre-trained language models fail in prediction tasks
Large pre-trained language models (LPLM) have shown spectacular success ...
research
∙
07/08/2022
Hidden Schema Networks
Most modern language models infer representations that, albeit powerful,...
research
∙
03/30/2022
A Novel First-Order Autoregressive Moving Average Model to Analyze Discrete-Time Series Irregularly Observed
A novel first-order autoregressive moving average model for analyzing di...
research
∙
10/27/2021
Dynamic Review-based Recommenders
Just as user preferences change with time, item reviews also reflect tho...
research
∙
05/20/2021
Nonlinear Hawkes Process with Gaussian Process Self Effects
Traditionally, Hawkes processes are used to model time–continuous point ...
research
∙
05/13/2021
An irregularly spaced first-order moving average model
A novel first-order moving-average model for analyzing time series obser...
research
∙
04/25/2021
Novel bivariate autoregressive model for predicting and forecasting irregularly observed time series
In several disciplines it is common to find time series measured at irre...
research
∙
12/10/2020
Recurrent Point Review Models
Deep neural network models represent the state-of-the-art methodologies ...
research
∙
12/09/2019
Recurrent Point Processes for Dynamic Review Models
Recent progress in recommender system research has shown the importance ...
research
∙
06/24/2019
Recurrent Adversarial Service Times
Service system dynamics occur at the interplay between customer behaviou...
research
∙
06/17/2017
