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07/11/2023
Objaverse-XL: A Universe of 10M+ 3D Objects
Natural language processing and 2D vision models have attained remarkabl...
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05/25/2023
Are Diffusion Models Vision-And-Language Reasoners?
Text-conditioned image generation models have recently shown immense qua...
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02/14/2023
Score-based Diffusion Models in Function Space
Diffusion models have recently emerged as a powerful framework for gener...
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12/18/2022
Plankton-FL: Exploration of Federated Learning for Privacy-Preserving Training of Deep Neural Networks for Phytoplankton Classification
Creating high-performance generalizable deep neural networks for phytopl...
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10/21/2022
Score-based Denoising Diffusion with Non-Isotropic Gaussian Noise Models
Generative models based on denoising diffusion techniques have led to an...
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08/16/2022
SMPL-IK: Learned Morphology-Aware Inverse Kinematics for AI Driven Artistic Workflows
Inverse Kinematics (IK) systems are often rigid with respect to their in...
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08/03/2022
Towards Generating Large Synthetic Phytoplankton Datasets for Efficient Monitoring of Harmful Algal Blooms
Climate change is increasing the frequency and severity of harmful algal...
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05/19/2022
Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation
Video prediction is a challenging task. The quality of video frames from...
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09/07/2021
Simple Video Generation using Neural ODEs
Despite having been studied to a great extent, the task of conditional g...
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06/24/2021
SALT: Sea lice Adaptive Lattice Tracking – An Unsupervised Approach to Generate an Improved Ocean Model
Warming oceans due to climate change are leading to increased numbers of...
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06/15/2021
Multi-Resolution Continuous Normalizing Flows
Recent work has shown that Neural Ordinary Differential Equations (ODEs)...
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06/07/2021
Improved Predictive Uncertainty using Corruption-based Calibration
We propose a simple post hoc calibration method to estimate the confiden...
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06/07/2021
Bias Mitigation of Face Recognition Models Through Calibration
Face recognition models suffer from bias: for example, the probability o...
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03/01/2021
Accounting for Variance in Machine Learning Benchmarks
Strong empirical evidence that one machine-learning algorithm A outperfo...
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06/30/2020
Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules
Robust perception relies on both bottom-up and top-down signals. Bottom-...
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07/31/2019
