BitBench: a benchmark for bitstream computing. - Kyle Daruwalla; Heng Zhuo; Carly Schulz; Mikko H. Lipasti (LCTES, 2019)

BitSAD v2: Compiler Optimization and Analysis for Bitstream Computing. - Kyle Daruwalla; Heng Zhuo; Rohit Shukla; Mikko H. Lipasti (ACM Trans. Archit. Code Optim., 2020)

Accelerating Deep Learning with Dynamic Data Pruning. - Ravi S. Raju; Kyle Daruwalla; Mikko H. Lipasti (CoRR, 2021)

Energy-Efficient Bayesian Inference Using Bitstream Computing. - Soroosh Khoram; Kyle Daruwalla; Mikko H. Lipasti (IEEE Comput. Archit. Lett., 2023)

Continual learning with the neural tangent ensemble. - Ari S. Benjamin; Christian-Gernot Pehle; Kyle Daruwalla (NeurIPS, 2024)

Information bottleneck-based Hebbian learning rule naturally ties working memory and synaptic updates. - Kyle Daruwalla; Mikko H. Lipasti (Frontiers Comput. Neurosci., 2024)

Delays in generalization match delayed changes in representational geometry. - Xingyu Zheng; Kyle Daruwalla; Ari S. Benjamin; David Klindt (UniReps, 2025)

Walking the Weight Manifold: a Topological Approach to Conditioning Inspired by Neuromodulation. - Ari S. Benjamin; Kyle Daruwalla; Christian Pehle; Anthony M. Zador (CoRR, 2025)