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06/30/2023
Topological Data Analysis Guided Segment Anything Model Prompt Optimization for Zero-Shot Segmentation in Biological Imaging
Emerging foundation models in machine learning are models trained on vas...
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06/16/2022
"Understanding Robustness Lottery": A Comparative Visual Analysis of Neural Network Pruning Approaches
Deep learning approaches have provided state-of-the-art performance in m...
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10/05/2019
Parallelizing Training of Deep Generative Models on Massive Scientific Datasets
Training deep neural networks on large scientific data is a challenging ...
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10/03/2019
Exploring Generative Physics Models with Scientific Priors in Inertial Confinement Fusion
There is significant interest in using modern neural networks for scient...
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09/25/2019
Function Preserving Projection for Scalable Exploration of High-Dimensional Data
We present function preserving projections (FPP), a scalable linear proj...
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07/19/2019
Scalable Topological Data Analysis and Visualization for Evaluating Data-Driven Models in Scientific Applications
With the rapid adoption of machine learning techniques for large-scale a...
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07/06/2019
Generative Counterfactual Introspection for Explainable Deep Learning
In this work, we propose an introspection technique for deep neural netw...
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01/15/2019
Separation and approximate separation of multipartite quantum gates
The number of qubits of current quantum computers is one of the most dom...
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12/19/2017
Exploring High-Dimensional Structure via Axis-Aligned Decomposition of Linear Projections
Two-dimensional embeddings remain the dominant approach to visualize hig...
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10/26/2017
