Dr. Jonathan Frankle
Chief Scientist
Verified Proof of Work Artifacts
2 items catalogedEach artifact below represents an authenticated research publication, production code repository, or technical architectural framework directly authored or co-created by Dr. Jonathan Frankle. Every entry undergoes editorial source verification.
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks
Authored the seminal ICLR 2019 Best Paper showing dense, randomly-initialized feed-forward networks contain subnetworks ('winning tickets') that—when trained in isolation from early initialization—reach test accuracy comparable to the original network in similar iterations.
Finding winning tickets requires iterative prune-and-retrain cycles, which is computationally heavier than standard one-pass training.
MPT-7B and MPT-30B: Commercial-Grade Open-Source Foundation Models
Led the engineering and open-weights release of MPT models trained with FlashAttention, ALiBi positional embeddings, and fast streaming data loaders, providing reproducible blueprints for sub-$200k foundation model pre-training.
ALiBi positional embeddings exhibit slight performance degradation compared to RoPE when scaled past 128k context windows.