Johan Bjorck

Affiliations:
  • Cornell University, Department of Computer Science, Ithaca, NY, USA (PhD 2021)


According to our database1, Johan Bjorck authored at least 28 papers between 2017 and 2025.

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Timeline

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Bibliography

2025
FLARE: Robot Learning with Implicit World Modeling.
CoRR, May, 2025

DreamGen: Unlocking Generalization in Robot Learning through Neural Trajectories.
CoRR, May, 2025

GR00T N1: An Open Foundation Model for Generalist Humanoid Robots.
CoRR, March, 2025

Scaling Optimal LR Across Token Horizons.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024
Scaling Optimal LR Across Token Horizon.
CoRR, 2024

Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.
CoRR, 2024

2023
Language Is Not All You Need: Aligning Perception with Language Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Image as a Foreign Language: BEIT Pretraining for Vision and Vision-Language Tasks.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language Tasks.
CoRR, 2022

Is High Variance Unavoidable in RL? A Case Study in Continuous Control.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Bootstrapping a high quality multilingual multimodal dataset for Bletchley.
Proceedings of the Asian Conference on Machine Learning, 2022

2021
Matrix factorization and Deep Learning in Scientific Domains: Understanding When and Why It Works.
PhD thesis, 2021

Towards Deeper Deep Reinforcement Learning.
CoRR, 2021

Low-Precision Reinforcement Learning.
CoRR, 2021

Towards Deeper Deep Reinforcement Learning with Spectral Normalization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Low-Precision Reinforcement Learning: Running Soft Actor-Critic in Half Precision.
Proceedings of the 38th International Conference on Machine Learning, 2021

Understanding Decoupled and Early Weight Decay.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Learning Augmented Methods for Matching: Improving Invasive Species Management and Urban Mobility.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Accelerating Ecological Sciences from Above: Spatial Contrastive Learning for Remote Sensing.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Characterizing the Loss Landscape in Non-Negative Matrix Factorization.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2019
Automatic Detection and Compression for Passive Acoustic Monitoring of the African Forest Elephant.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Understanding Batch Normalization.
CoRR, 2018

Phase Mapper: Accelerating Materials Discovery with AI.
AI Mag., 2018

Understanding Batch Normalization.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Scalable Relaxations of Sparse Packing Constraints: Optimal Biocontrol in Predator-Prey Networks.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Scalable Relaxations of Sparse Packing Constraints: Optimal Biocontrol in Predator-Prey Network.
CoRR, 2017

Relaxation Methods for Constrained Matrix Factorization Problems: Solving the Phase Mapping Problem in Materials Discovery.
Proceedings of the Integration of AI and OR Techniques in Constraint Programming, 2017

Phase-Mapper: An AI Platform to Accelerate High Throughput Materials Discovery.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017


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