1 citations · 1 across the 8 of their papers we have counts for
10 papers
Elliptic Loss Regularization
Ali Hasan, Haoming Yang, Yuting Ng +1
Regularizing neural networks is important for anticipating model behavior in regions of the data space that are not well represented. In this work, we propose a regularization tech…
Distributionally Robust Optimization as a Scalable Framework to Characterize Extreme Value Distributions
Patrick Kuiper, Ali Hasan, Wenhao Yang +4
The goal of this paper is to develop distributionally robust optimization (DRO) estimators, specifically for multidimensional Extreme Value Theory (EVT) statistics. EVT supports us…
Neural McKean-Vlasov Processes: Distributional Dependence in Diffusion Processes
Haoming Yang, Ali Hasan, Yuting Ng +1
McKean-Vlasov stochastic differential equations (MV-SDEs) provide a mathematical description of the behavior of an infinite number of interacting particles by imposing a dependence…
Perceiver-based CDF Modeling for Time Series Forecasting
Cat P. Le, Chris Cannella, Ali Hasan +2
Transformers have demonstrated remarkable efficacy in forecasting time series data. However, their extensive dependence on self-attention mechanisms demands significant computation…
Treatment Effects in Extreme Regimes
Ahmed Aloui, Ali Hasan, Yuting Ng +2
Understanding treatment effects in extreme regimes is important for characterizing risks associated with different interventions. This is hindered by the unavailability of counterf…
Inference and Sampling of Point Processes from Diffusion Excursions
Ali Hasan, Yu Chen, Yuting Ng +3
Point processes often have a natural interpretation with respect to a continuous process. We propose a point process construction that describes arrival time observations in terms…
Inference and Sampling for Archimax Copulas
Yuting Ng, Ali Hasan, Vahid Tarokh
Understanding multivariate dependencies in both the bulk and the tails of a distribution is an important problem for many applications, such as ensuring algorithms are robust to ob…
Generative Archimedean Copulas
Yuting Ng, Ali Hasan, Khalil Elkhalil +1
We propose a new generative modeling technique for learning multidimensional cumulative distribution functions (CDFs) in the form of copulas. Specifically, we consider certain clas…
Modeling Extremes with d-max-decreasing Neural Networks
Ali Hasan, Khalil Elkhalil, Yuting Ng +4
We propose a novel neural network architecture that enables non-parametric calibration and generation of multivariate extreme value distributions (MEVs). MEVs arise from Extreme Va…
Robust Marine Buoy Placement for Ship Detection Using Dropout K-Means
Yuting Ng, João M. Pereira, Denis Garagic +1
Marine buoys aid in the battle against Illegal, Unreported and Unregulated (IUU) fishing by detecting fishing vessels in their vicinity. Marine buoys, however, may be disrupted by…