110 citations · 387 across the 46 of their papers we have counts for
6 papers · 1 filter
Hybrid Generative Modeling for Incomplete Physics: Deep Grey-Box Meets Optimal Transport
Gurjeet Sangra Singh, Maciej Falkiewicz, Alexandros Kalousis
Physics phenomena are often described by ordinary and/or partial differential equations (ODEs/PDEs), and solved analytically or numerically. Unfortunately, many real-world systems…
Kolmogorov-Smirnov GAN
Maciej Falkiewicz, Naoya Takeishi, Alexandros Kalousis
We propose a novel deep generative model, the Kolmogorov-Smirnov Generative Adversarial Network (KSGAN). Unlike existing approaches, KSGAN formulates the learning process as a mini…
Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability
Maciej Falkiewicz, Naoya Takeishi, Imahn Shekhzadeh +4
Bayesian inference allows expressing the uncertainty of posterior belief under a probabilistic model given prior information and the likelihood of the evidence. Predominantly, the…
Structured nonlinear variable selection
Magda Gregorová, Alexandros Kalousis, Stéphane Marchand-Maillet
We investigate structured sparsity methods for variable selection in regression problems where the target depends nonlinearly on the inputs. We focus on general nonlinear functions…
Learning Predictive Leading Indicators for Forecasting Time Series Systems with Unknown Clusters of Forecast Tasks
Magda Gregorova, Alexandros Kalousis, Stephane Marchand-Maillet
We present a new method for forecasting systems of multiple interrelated time series. The method learns the forecast models together with discovering leading indicators from within…
Lifelong Generative Modeling
Jason Ramapuram, Magda Gregorova, Alexandros Kalousis
Lifelong learning is the problem of learning multiple consecutive tasks in a sequential manner, where knowledge gained from previous tasks is retained and used to aid future learni…