no code implementations • CVPR 2024 • Aaron Gokaslan, A. Feder Cooper, Jasmine Collins, Landan Seguin, Austin Jacobson, Mihir Patel, Jonathan Frankle, Cory Stephenson, Volodymyr Kuleshov
We then develop a data- and compute-efficient training recipe that requires as little as 3% of the LAION data (i. e. roughly 70 million examples) needed to train existing SD2 models but obtains the same quality.
1 code implementation • 25 Oct 2023 • Aaron Gokaslan, A. Feder Cooper, Jasmine Collins, Landan Seguin, Austin Jacobson, Mihir Patel, Jonathan Frankle, Cory Stephenson, Volodymyr Kuleshov
This task presents two challenges: (1) high-resolution CC images lack the captions necessary to train text-to-image generative models; (2) CC images are relatively scarce.
no code implementations • 5 Jan 2023 • Jasmine Collins, Anqi Liang, Jitendra Malik, Hao Zhang, Frédéric Devernay
We present a neural network approach to transfer the motion from a single image of an articulated object to a rest-state (i. e., unarticulated) 3D model.
1 code implementation • 16 Jun 2022 • Eliza Kosoy, David M. Chan, Adrian Liu, Jasmine Collins, Bryanna Kaufmann, Sandy Han Huang, Jessica B. Hamrick, John Canny, Nan Rosemary Ke, Alison Gopnik
Recent work in machine learning and cognitive science has suggested that understanding causal information is essential to the development of intelligence.
no code implementations • 21 Feb 2022 • Eliza Kosoy, Adrian Liu, Jasmine Collins, David M Chan, Jessica B Hamrick, Nan Rosemary Ke, Sandy H Huang, Bryanna Kaufmann, John Canny, Alison Gopnik
Despite recent progress in reinforcement learning (RL), RL algorithms for exploration still remain an active area of research.
no code implementations • CVPR 2023 • Rui Guo, Jasmine Collins, Oscar de Lima, Andrew Owens
Our model learns to camouflage a variety of object shapes from randomly sampled locations and viewpoints within the input scene, and is the first to address the problem of hiding complex object shapes.
1 code implementation • CVPR 2022 • Jasmine Collins, Shubham Goel, Kenan Deng, Achleshwar Luthra, Leon Xu, Erhan Gundogdu, Xi Zhang, Tomas F. Yago Vicente, Thomas Dideriksen, Himanshu Arora, Matthieu Guillaumin, Jitendra Malik
ABO contains product catalog images, metadata, and artist-created 3D models with complex geometries and physically-based materials that correspond to real, household objects.
1 code implementation • 6 May 2020 • Eliza Kosoy, Jasmine Collins, David M. Chan, Sandy Huang, Deepak Pathak, Pulkit Agrawal, John Canny, Alison Gopnik, Jessica B. Hamrick
Research in developmental psychology consistently shows that children explore the world thoroughly and efficiently and that this exploration allows them to learn.
1 code implementation • 3 Mar 2019 • Jasmine Collins, Johannes Balle, Jonathon Shlens
We find that a standardization loss accelerates training on both small- and large-scale image classification experiments, works with a variety of architectures, and is largely robust to training across different batch sizes.
1 code implementation • 29 Nov 2016 • Jasmine Collins, Jascha Sohl-Dickstein, David Sussillo
They can store an amount of task information which is linear in the number of parameters, and is approximately 5 bits per parameter.
no code implementations • 4 Nov 2016 • Akosua Busia, Jasmine Collins, Navdeep Jaitly
We first train a series of deep neural networks to predict eight-class secondary structure labels given a protein's amino acid sequence information and find that using recent methods for regularization, such as dropout and weight-norm constraining, leads to measurable gains in accuracy.
Protein Secondary Structure Prediction
Protein Structure Prediction