Deterministic Boltzmann machine VLSI can be scaled using multi-chip modules. - Michael Murray; James B. Burr; David G. Stork; Ming-Tak Leung; Kan Boonyanit; Gregory J. Wolff; Allen M. Peterson (ASAP, 1992)

Digital Boltzmann VLSI for Constraint Satisfaction and Learning. - Michael Murray; Ming-Tak Leung; Kan Boonyanit; Kong Kritayakirana; James B. Burr; Gregory J. Wolff; Tokahiro Watanabe; Edward L. Schwartz; David G. Stork; Allen M. Peterson (NIPS, 1993)

Exchange Your Outlook - A University Migration or: "the outlook's so bright, I gotta wear shades?". - Michael Murray; Michael Quiner; Michael Critchfield (SIGUCCS, 1998)

A Help Desk Prescription - Curing Ills with a Dose of Remedy. - Michael Critchfield; Michael Murray; Michael Lewis 003; Jason Musselman (SIGUCCS, 1999)

Ills Cured with a Dose of Remedy. - Michael Critchfield; Michael Murray (SIGUCCS, 2000)

Reviewing Policy, Practice and Potential of e-Consultation in Northern Ireland and the Republic of Ireland - A European Case Study. - G. Honor Fagan; Michael Murray; Paul McCusker (ECEG, 2005)

'Digitally Renewing Democracy'? The Potential for eConsultation in Northern Ireland and the Republic of Ireland. - G. Honor Fagan; Michael Murray; Paul McCusker (EGOV (Workshops and Posters), 2005)

Computer Security Incident Response Team Development and Evolution. - Robin Ruefle; Audrey J. Dorofee; David A. Mundie; Allen D. Householder; Michael Murray; Samuel J. Perl (IEEE Secur. Priv., 2014)

Promoting Comprehension of Health Information among Older Adults. - Jessie Chin; Jessica Johnson; Darcie Moeller; Elise Duwe; James Graumlich; Michael Murray; Elizabeth A. L. Stine-Morrow; Daniel G. Morrow (CogSci, 2015)

Deep CNN Sparse Coding Analysis: Towards Average Case. - Michael Murray; Jared Tanner (DSW, 2018)

Towards an understanding of CNNs: analysing the recovery of activation pathways via Deep Convolutional Sparse Coding. - Michael Murray; Jared Tanner (CoRR, 2018)

An experimental comparison of classification techniques in debt recoveries scoring: Evidence from South Africa's unsecured lending market. - Jonah Mushava; Michael Murray (Expert Syst. Appl., 2018)

Vision-and-Dialog Navigation. - Jesse Thomason; Michael Murray; Maya Cakmak; Luke Zettlemoyer (CoRL, 2019)

The Permuted Striped Block Model and its Factorization - Algorithms with Recovery Guarantees. - Michael Murray; Jared Tanner (CoRR, 2020)

Learning Backchanneling Behaviors for a Social Robot via Data Augmentation from Human-Human Conversations. - Michael Murray; Nick Walker 001; Amal Nanavati; Patrícia Alves-Oliveira; Nikita Filippov; Allison Sauppé; Bilge Mutlu; Maya Cakmak (CoRL, 2021)

Activation function design for deep networks: linearity and effective initialisation. - Michael Murray; Vinayak Abrol; Jared Tanner (CoRR, 2021)

Transjugular intrahepatic portosystemic shunt (TIPS) procedure: an assessment of the quality and readability of online information. - Sean-Tee J. M. Lim; Martin Kelly; Logeswaran Selvarajah; Michael Murray; Timothy Scanlon (BMC Medical Informatics Decis. Mak., 2021)

From matrix factorisation to signal propagation in deep learning: algorithms and guarantees. - Michael Murray (2021)

A novel XGBoost extension for credit scoring class-imbalanced data combining a generalized extreme value link and a modified focal loss function. - Jonah Mushava; Michael Murray (Expert Syst. Appl., 2022)

Following Natural Language Instructions for Household Tasks With Landmark Guided Search and Reinforced Pose Adjustment. - Michael Murray; Maya Cakmak (IEEE Robotics Autom. Lett., 2022)

Encoder Blind Combinatorial Compressed Sensing. - Michael Murray; Jared Tanner (IEEE Trans. Inf. Theory, 2022)

Tell Me About It: Adolescent Self-Disclosure with an Online Robot for Mental Health. - Tony W. Li; Michael Murray; Zander Brumbaugh; Raida Karim; Hanna Lee; Maya Cakmak; Elin A. Björling (HRI (Companion), 2023)

Characterizing the spectrum of the NTK via a power series expansion. - Michael Murray; Hui Jin; Benjamin Bowman; Guido Montúfar (ICLR, 2023)

Training shallow ReLU networks on noisy data using hinge loss: when do we overfit and is it benign? - Erin George; Michael Murray; William Swartworth; Deanna Needell (NeurIPS, 2023)

Low-Effort, Unqualified, and Malicious User Behaviors in Online Human-Robot Interaction Studies. - Tony W. Li; Yelin Jo; Zander Brumbaugh; Hanna Lee; Michael Murray; Elin A. Björling (SIGDOC, 2023)

Framework of the Centralized Interactive Phenomics Resource (CIPHER) standard for electronic health data-based phenomics knowledgebase. - Jacqueline Honerlaw; Yuk-Lam Ho; Francesca Fontin; Jeffrey Gosian; Monika Maripuri; Michael Murray; Rahul Sangar; Ashley Galloway; Andrew J. Zimolzak; Stacey B. Whitbourne; Juan P. Casas; Rachel B. Ramoni; et al. (J. Am. Medical Informatics Assoc., 2023)

Teaching Robots with Show and Tell: Using Foundation Models to Synthesize Robot Policies from Language and Visual Demonstration. - Michael Murray; Abhishek Gupta; Maya Cakmak (CoRL, 2024)

Learning to Grasp in Clutter with Interactive Visual Failure Prediction. - Michael Murray; Abhishek Gupta; Maya Cakmak (ICRA, 2024)

Diffusion-PbD: Generalizable Robot Programming by Demonstration with Diffusion Features. - Michael Murray; Entong Su; Maya Cakmak (IROS, 2024)

Benign overfitting in leaky ReLU networks with moderate input dimension. - Kedar Karhadkar; Erin George; Michael Murray; Guido F. Montúfar; Deanna Needell (NeurIPS, 2024)

Bounds for the smallest eigenvalue of the NTK for arbitrary spherical data of arbitrary dimension. - Kedar Karhadkar; Michael Murray; Guido F. Montúfar (NeurIPS, 2024)

Centralized Interactive Phenomics Resource: an integrated online phenomics knowledgebase for health data users. - Jacqueline Honerlaw; Yuk-Lam Ho; Francesca Fontin; Michael Murray; Ashley Galloway; David Heise; Keith Connatser; Laura Davies; Jeffrey Gosian; Monika Maripuri; John Russo 001; Rahul Sangar; et al. (J. Am. Medical Informatics Assoc., 2024)

Mildly Overparameterized ReLU Networks Have a Favorable Loss Landscape. - Kedar Karhadkar; Michael Murray; Hanna Tseran; Guido Montúfar (Trans. Mach. Learn. Res., 2024)

Flexible loss functions for binary classification in gradient-boosted decision trees: An application to credit scoring. - Jonah Mushava; Michael Murray (Expert Syst. Appl., 2024)