Deep Learning
'Tell me what happened, I won't judge': how AI helped me listen to myself Nathan Filer
It was past midnight and I was awake, scrolling through WhatsApp group messages I'd sent earlier. I'd been trying to be funny, quick, effervescent. But each message now felt like too much. I'd overreached again – said more than I should, said it wrong. I had that familiar ache of feeling overexposed and ridiculous.
Tight Lower Bounds on Worst-Case Guarantees for Zero-Shot Learning with Attributes
We develop a rigorous mathematical analysis of zero-shot learning with attributes.
Partition and Code: learning how to compress graphs
Can we use machine learning to compress graph data?
Isometric 3D Adversarial Examples in the Physical World Yibo Miao
Based on Definitions 1 and 2, we have the following theorem.
c4ede56bbd98819ae6112b20ac6bf145-Paper.pdf
The idea of federated learning is to collaboratively train a neural network on a server.
All Tokens Matter: Token Labeling for Training Better Vision Transformers
The result can be further increased to 86.4% by slightly scaling the
Fitting summary statistics of neural data with a differentiable spiking network simulator
Fitting network models to neural activity is an important tool in neuroscience.
Neural Distance Embeddings for Biological Sequences
The vector space can then be used to study the relationship between sequences and, potentially, decode new ones (see Section 7.2). On the right, an example of the hierarchical clustering produced on the Poincaré disk.