11 citations · 22 across the 12 of their papers we have counts for
12 papers
AutoSizer: Automatic Sizing of Analog and Mixed-Signal Circuits via Large Language Model (LLM) Agents
Xi Yu, Dmitrii Torbunov, Soumyajit Mandal +1
The design of Analog and Mixed-Signal (AMS) integrated circuits remains heavily reliant on expert knowledge, with transistor sizing a major bottleneck due to nonlinear behavior, hi…
Parameter Inference and Uncertainty Quantification with Diffusion Models: Extending CDI to 2D Spatial Conditioning
Dmitrii Torbunov, Yihui Ren, Lijun Wu +1
Uncertainty quantification is critical in scientific inverse problems to distinguish identifiable parameters from those that remain ambiguous given available measurements. The Cond…
IE2Video: Adapting Pretrained Diffusion Models for Event-Based Video Reconstruction
Dmitrii Torbunov, Onur Okuducu, Yi Huang +4
Continuous video monitoring in surveillance, robotics, and wearable systems faces a fundamental power constraint: conventional RGB cameras consume substantial energy through fixed-…
Robust and Generalizable Background Subtraction on Images of Calorimeter Jets using Unsupervised Generative Learning
Yeonju Go, Dmitrii Torbunov, Yi Huang +8
Accurate separation of signal from background is one of the main challenges for precision measurements across high-energy and nuclear physics. Conventional supervised learning meth…
CircuitSense: A Hierarchical MLLM Benchmark Bridging Visual Comprehension and Symbolic Reasoning in Engineering Design Process
Arman Akbari, Jian Gao, Yifei Zou +6
Engineering design operates through hierarchical abstraction from system specifications to component implementations, requiring visual understanding coupled with mathematical reaso…
EvRT-DETR: Latent Space Adaptation of Image Detectors for Event-based Vision
Dmitrii Torbunov, Yihui Ren, Animesh Ghose +2
Event-based cameras (EBCs) have emerged as a bio-inspired alternative to traditional cameras, offering advantages in power efficiency, temporal resolution, and high dynamic range.…
Diffusion Model-based Parameter Estimation in Dynamic Power Systems
Feiqin Zhu, Dmitrii Torbunov, Zhongjing Jiang +4
Parameter estimation, which represents a classical inverse problem, is often ill-posed as different parameter combinations can yield identical outputs. This non-uniqueness presents…
Effectiveness of denoising diffusion probabilistic models for fast and high-fidelity whole-event simulation in high-energy heavy-ion experiments
Yeonju Go, Dmitrii Torbunov, Timothy Rinn +6
Artificial intelligence (AI) generative models, such as generative adversarial networks (GANs), variational auto-encoders, and normalizing flows, have been widely used and studied…
Unpaired Image Translation to Mitigate Domain Shift in Liquid Argon Time Projection Chamber Detector Responses
Yi Huang, Dmitrii Torbunov, Brett Viren +4
Deep learning algorithms often are trained and deployed on different datasets. Any systematic difference between the training and a test dataset may degrade the algorithm performan…
UVCGAN v2: An Improved Cycle-Consistent GAN for Unpaired Image-to-Image Translation
Dmitrii Torbunov, Yi Huang, Huan-Hsin Tseng +6
An unpaired image-to-image (I2I) translation technique seeks to find a mapping between two domains of data in a fully unsupervised manner. While initial solutions to the I2I proble…
Solving Simulation Systematics in and with AI/ML
Brett Viren, Jin Huang, Yi Huang +5
Training an AI/ML system on simulated data while using that system to infer on data from real detectors introduces a systematic error which is difficult to estimate and in many ana…
UVCGAN: UNet Vision Transformer cycle-consistent GAN for unpaired image-to-image translation
Dmitrii Torbunov, Yi Huang, Haiwang Yu +5
Unpaired image-to-image translation has broad applications in art, design, and scientific simulations. One early breakthrough was CycleGAN that emphasizes one-to-one mappings betwe…