Iacopo Poli

Orcid: 0000-0002-0964-0624

According to our database1, Iacopo Poli authored at least 15 papers between 2019 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2022
RITA: a Study on Scaling Up Generative Protein Sequence Models.
CoRR, 2022

PAGnol: An Extra-Large French Generative Model.
Proceedings of the Thirteenth Language Resources and Evaluation Conference, 2022

Adversarial Robustness by Design Through Analog Computing And Synthetic Gradients.
Proceedings of the IEEE International Conference on Acoustics, 2022

2021
Is the Number of Trainable Parameters All That Actually Matters?
CoRR, 2021

ROPUST: Improving Robustness through Fine-tuning with Photonic Processors and Synthetic Gradients.
CoRR, 2021

Contrastive Embeddings for Neural Architectures.
CoRR, 2021

Photonic Differential Privacy with Direct Feedback Alignment.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Photonic co-processors in HPC: Using LightOn OPUs for Randomized Numerical Linear Algebra.
Proceedings of the IEEE Hot Chips 33 Symposium, 2021

LightOn Optical Processing Unit : Scaling-up AI and HPC with a Non von Neumann co-processor.
Proceedings of the IEEE Hot Chips 33 Symposium, 2021

2020
NEWMA: A New Method for Scalable Model-Free Online Change-Point Detection.
IEEE Trans. Signal Process., 2020

Hardware Beyond Backpropagation: a Photonic Co-Processor for Direct Feedback Alignment.
CoRR, 2020

Online Change Point Detection in Molecular Dynamics With Optical Random Features.
CoRR, 2020

Light-in-the-loop: using a photonics co-processor for scalable training of neural networks.
CoRR, 2020

Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
Principled Training of Neural Networks with Direct Feedback Alignment.
CoRR, 2019


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