Scholar
Nolan Dey
Google Scholar ID: JHUfMr0AAAAJ
Cerebras Systems
Large language models
Training efficiency
Sparsity
Explainable AI
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Citations & Impact
All-time
Citations
449
H-index
6
i10-index
5
Publications
16
Co-authors
6
list available
Publications
8 items
Don't Drop Dropout: Optimizing Layer Sparsity for Efficient LLM Training and Inference
2026
Cited
0
Unlocking Lossless Speedups in LLMs via Discrete Diffusion
2026
Cited
0
Predicting Training Re-evaluation Curves Enables Effective Data Curriculums for LLMs
2025
Cited
0
Scaling with Collapse: Efficient and Predictable Training of LLM Families
2025
Cited
0
Power Lines: Scaling Laws for Weight Decay and Batch Size in LLM Pre-training
2025
Cited
0
Don't be lazy: CompleteP enables compute-efficient deep transformers
2025
Cited
0
Straight to Zero: Why Linearly Decaying the Learning Rate to Zero Works Best for LLMs
2025
Cited
1
Neuron-based explanations of neural networks sacrifice completeness and interpretability
2020
Cited
0
Co-authors
5 total
Joel Hestness
Distinguished Research Scientist, Cerebras Systems
Daria Soboleva
Cerebras Systems
Shane Bergsma
Cerebras Systems
Graham Taylor
University of Guelph and Vector Institute for Artificial Intelligence
Alexander Wong
Canada Research Chair FIET FInstP FRSPH FRSM FRGS FGS FRSA FISDDE, University of Waterloo
