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Found 5 papers, 2 papers with code
L2SR: Learning to Sample and Reconstruct for Accelerated MRI via Reinforcement Learning
In this paper, we propose an alternating training framework for jointly learning a good pair of samplers and reconstructors via deep reinforcement learning (RL).
Climate uncertainty impacts on optimal mitigation pathways and social cost of carbon
CO2 emissions trajectories resulting from the optimal level of emissions abatement in all pathways are also sensitive to climate uncertainty, with 2050 emissions ranging from -12 to +14 GtCO2/yr in the 1. 5C scenario.
Deep Multi-Modal Sets
Most deep learning-based methods rely on a late fusion technique whereby multiple feature types are encoded and concatenated and then a multi layer perceptron (MLP) combines the fused embedding to make predictions.
A frequency domain analysis of gradient-based adversarial examples
And the log-spectrum difference of the adversarial examples and clean image is more concentrated in the high-frequency part than the low-frequency part.
A Tale of Tails: Model Collapse as a Change of Scaling Laws
We discover a wide range of decay phenomena, analyzing loss of scaling, shifted scaling with number of generations, the ''un-learning" of skills, and grokking when mixing human and synthesized data.
