Johan Bjorck

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


According to our database1, Johan Bjorck authored at least 22 papers between 2017 and 2023.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

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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