Abhilasha Dave

According to our database, Abhilasha Dave authored at least 6 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Hardware-Aware Tensor Networks for Real-Time Quantum-Inspired Anomaly Detection at Particle Colliders.

Sagar Addepalli, Prajita Bhattarai, Abhilasha Dave, Julia Gonski

CoRR, March, 2026

Machine Learning on Heterogeneous, Edge, and Quantum Hardware for Particle Physics (ML-HEQUPP).

Julia Gonski, Jenni Ott, Shiva Abbaszadeh, Sagar Addepalli, Matteo Cremonesi, Jennet Dickinson, Giuseppe Di Guglielmo, Erdem Yigit Ertorer, Lindsey Gray, Ryan Herbst, Christian Herwig, Tae Min Hong, Benedikt Maier, Maryam Bayat Makou, David Miller, Mark S. Neubauer, Cristián Peña, Dylan Rankin, Seon-Hee Seo, Giordon Stark, Alexander Tapper, Audrey Corbeil Therrien, Ioannis Xiotidis, Keisuke Yoshihara, G. Abarajithan, Nural Akchurin, Carlos Argüelles, Saptaparna Bhattacharya, Lorenzo Borella, Christian Boutan, Tom Braine, James Brau, Martin Breidenbach, Antonio Chahine, Talal Ahmed Chowdhury, Yuan-Tang Chou, Seokju Chung, Alberto Coppi, Mariarosaria D'Alfonso, Abhilasha Dave, Chance Desmet, Angela Di Fulvio, Karri DiPetrillo, Javier Duarte, Auralee Edelen, Jan Eysermans, Yongbin Feng, Emmett Forrestel, Dolores Garcia, Loredana Gastaldo, Julián García Pardiñas, Lino Gerlach, Loukas Gouskos, Katya Govorkova, Carl Grace, Christopher Grant, Philip Harris, Ciaran Hasnip, Timon Heim, Abraham Holtermann, Gian Michele Innocenti, Koji Ishidoshiro, Miaochen Jin, Jyothisraj Johnson, Stephen Jones, Andreas Jung, Georgia Karagiorgi, Ryan Kastner, Nicholas Kamp, Doojin Kim, Kyoungchul Kong, Katie Kudela, Jelena Lalic, Bo-Cheng Lai, Yun-Tsung Lai, Tommy Lam, Jeffrey Lazar, Aobo Li, Zepeng Li, Haoyun Liu, Vladimir Loncar, Luca Macchiarulo, Christopher Madrid, Zhenghua Ma, Prashansa Mukim, Victoria Nguyen, Sungbin Oh, Isobel Ojalvo, Hideyoshi Ozaki, Simone Pagan Griso, Myeonghun Park, Christoph Paus, Santosh Parajuli, Benjamin Parpillon, Sara Pozzi, Ema Puljak

CoRR, February, 2026

2025

Neural Network Acceleration on MPSoC board: Integrating SLAC's SNL, Rogue Software and Auto-SNL.

Hamza Ezzaoui Rahali, Abhilasha Dave, Larry Ruckman, Mohammad Mehdi Rahimifar, Audrey C. Therrien, James J. Russel, Ryan Herbst

CoRR, August, 2025

FPGA-Accelerated SpeckleNN with SNL for Real-time X-ray Single-Particle Imaging.

Abhilasha Dave, Cong Wang, James Russell, Ryan Herbst, Jana Thayer

CoRR, February, 2025

2024

Analysis of Hardware Synthesis Strategies for Machine Learning in Collider Trigger and Data Acquisition.

Haoyi Jia, Abhilasha Dave, Julia Gonski, Ryan Herbst

CoRR, 2024

2023

HW/SW Codesign for Approximation-Aware Binary Neural Networks.

Abhilasha Dave, Fabio Frustaci, Fanny Spagnolo, Mikail Yayla, Jian-Jia Chen, Hussam Amrouch

IEEE J. Emerg. Sel. Topics Circuits Syst., March, 2023