Search Results for author: Valerio Pascucci

Found 7 papers, 3 papers with code

AVA: Towards Autonomous Visualization Agents through Visual Perception-Driven Decision-Making

no code implementations7 Dec 2023 Shusen Liu, Haichao Miao, Zhimin Li, Matthew Olson, Valerio Pascucci, Peer-Timo Bremer

With recent advances in multi-modal foundation models, the previously text-only large language models (LLM) have evolved to incorporate visual input, opening up unprecedented opportunities for various applications in visualization.

Decision Making

Instance-wise Linearization of Neural Network for Model Interpretation

no code implementations25 Oct 2023 Zhimin Li, Shusen Liu, Kailkhura Bhavya, Timo Bremer, Valerio Pascucci

For a neural network model, the non-linear behavior is often caused by non-linear activation units of a model.

Dimensionality Reduction

"Understanding Robustness Lottery": A Geometric Visual Comparative Analysis of Neural Network Pruning Approaches

no code implementations16 Jun 2022 Zhimin Li, Shusen Liu, Xin Yu, Kailkhura Bhavya, Jie Cao, Diffenderfer James Daniel, Peer-Timo Bremer, Valerio Pascucci

We decomposed and evaluated a set of critical geometric concepts from the common adopted classification loss, and used them to design a visualization system to compare and highlight the impact of pruning on model performance and feature representation.

Network Pruning

NViSII: A Scriptable Tool for Photorealistic Image Generation

2 code implementations28 May 2021 Nathan Morrical, Jonathan Tremblay, Yunzhi Lin, Stephen Tyree, Stan Birchfield, Valerio Pascucci, Ingo Wald

We present a Python-based renderer built on NVIDIA's OptiX ray tracing engine and the OptiX AI denoiser, designed to generate high-quality synthetic images for research in computer vision and deep learning.

Image Generation Optical Flow Estimation +1

Ray Tracing Structured AMR Data Using ExaBricks

1 code implementation7 Sep 2020 Ingo Wald, Stefan Zellmann, Will Usher, Nate Morrical, Ulrich Lang, Valerio Pascucci

Structured Adaptive Mesh Refinement (Structured AMR) enables simulations to adapt the domain resolution to save computation and storage, and has become one of the dominant data representations used by scientific simulations; however, efficiently rendering such data remains a challenge.

Graphics Data Structures and Algorithms

Visual Interrogation of Attention-Based Models for Natural Language Inference and Machine Comprehension

no code implementations EMNLP 2018 Shusen Liu, Tao Li, Zhimin Li, Vivek Srikumar, Valerio Pascucci, Peer-Timo Bremer

Neural networks models have gained unprecedented popularity in natural language processing due to their state-of-the-art performance and the flexible end-to-end training scheme.

Decision Making Natural Language Inference +1

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