Kyle Daruwalla

According to our database, Kyle Daruwalla authored at least 6 papers between 2019 and 2024.

Collaborative distances:

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

2024

Information bottleneck-based Hebbian learning rule naturally ties working memory and synaptic updates.

Kyle Daruwalla, Mikko H. Lipasti

Frontiers Comput. Neurosci., 2024

Continual learning with the neural tangent ensemble.

Ari S. Benjamin, Christian-Gernot Pehle, Kyle Daruwalla

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Energy-Efficient Bayesian Inference Using Bitstream Computing.

Soroosh Khoram, Kyle Daruwalla, Mikko H. Lipasti

IEEE Comput. Archit. Lett., 2023

2021

Accelerating Deep Learning with Dynamic Data Pruning.

Ravi S. Raju, Kyle Daruwalla, Mikko H. Lipasti

CoRR, 2021

2020

BitSAD v2: Compiler Optimization and Analysis for Bitstream Computing.

Kyle Daruwalla, Heng Zhuo, Rohit Shukla, Mikko H. Lipasti

ACM Trans. Archit. Code Optim., 2020

2019

BitBench: a benchmark for bitstream computing.

Kyle Daruwalla, Heng Zhuo, Carly Schulz, Mikko H. Lipasti

Proceedings of the 20th ACM SIGPLAN/SIGBED International Conference on Languages, 2019