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06/21/2023
Constant Memory Attention Block
Modern foundation model architectures rely on attention mechanisms to ef...
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05/23/2023
Constant Memory Attentive Neural Processes
Neural Processes (NPs) are efficient methods for estimating predictive u...
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11/15/2022
Latent Bottlenecked Attentive Neural Processes
Neural Processes (NPs) are popular methods in meta-learning that can est...
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11/09/2022
Training a Vision Transformer from scratch in less than 24 hours with 1 GPU
Transformers have become central to recent advances in computer vision. ...
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06/17/2022
Stop Overcomplicating Selective Classification: Use Max-Logit
We tackle the problem of Selective Classification where the goal is to a...
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05/17/2022
Monotonicity Regularization: Improved Penalties and Novel Applications to Disentangled Representation Learning and Robust Classification
We study settings where gradient penalties are used alongside risk minim...
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06/20/2021
TD-GEN: Graph Generation With Tree Decomposition
We propose TD-GEN, a graph generation framework based on tree decomposit...
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02/25/2021
Variational Selective Autoencoder: Learning from Partially-Observed Heterogeneous Data
Learning from heterogeneous data poses challenges such as combining data...
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01/17/2020
Adapting Grad-CAM for Embedding Networks
The gradient-weighted class activation mapping (Grad-CAM) method can fai...
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10/02/2019
Graph Generation with Variational Recurrent Neural Network
Generating graph structures is a challenging problem due to the diverse ...
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06/30/2015
Learning to Detect Blue-white Structures in Dermoscopy Images with Weak Supervision
We propose a novel approach to identify one of the most significant derm...
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02/12/2015
Discovering Human Interactions in Videos with Limited Data Labeling
We present a novel approach for discovering human interactions in videos...
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02/06/2015
Visual Recognition by Counting Instances: A Multi-Instance Cardinality Potential Kernel
Many visual recognition problems can be approached by counting instances...
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09/26/2013
