Search Results for author: Kristy Choi

Found 15 papers, 5 papers with code

Concrete Score Matching: Generalized Score Matching for Discrete Data

no code implementations2 Nov 2022 Chenlin Meng, Kristy Choi, Jiaming Song, Stefano Ermon

To this end, we propose an analogous score function called the "Concrete score", a generalization of the (Stein) score for discrete settings.

Density Estimation

LMPriors: Pre-Trained Language Models as Task-Specific Priors

no code implementations22 Oct 2022 Kristy Choi, Chris Cundy, Sanjari Srivastava, Stefano Ermon

Particularly in low-data regimes, an outstanding challenge in machine learning is developing principled techniques for augmenting our models with suitable priors.

Causal Inference Common Sense Reasoning +3

ButterflyFlow: Building Invertible Layers with Butterfly Matrices

no code implementations28 Sep 2022 Chenlin Meng, Linqi Zhou, Kristy Choi, Tri Dao, Stefano Ermon

Normalizing flows model complex probability distributions using maps obtained by composing invertible layers.

Density Estimation

Counterbalancing Teacher: Regularizing Batch Normalized Models for Robustness

no code implementations4 Jul 2022 Saeid Asgari Taghanaki, Ali Gholami, Fereshte Khani, Kristy Choi, Linh Tran, Ran Zhang, Aliasghar Khani

Batch normalization (BN) is a ubiquitous technique for training deep neural networks that accelerates their convergence to reach higher accuracy.

Density Ratio Estimation via Infinitesimal Classification

1 code implementation22 Nov 2021 Kristy Choi, Chenlin Meng, Yang song, Stefano Ermon

We then estimate the instantaneous rate of change of the bridge distributions indexed by time (the "time score") -- a quantity defined analogously to data (Stein) scores -- with a novel time score matching objective.

Classification Density Ratio Estimation +1

Featurized Density Ratio Estimation

1 code implementation5 Jul 2021 Kristy Choi, Madeline Liao, Stefano Ermon

Density ratio estimation serves as an important technique in the unsupervised machine learning toolbox.

Data Augmentation Density Ratio Estimation +1

Robust Representation Learning via Perceptual Similarity Metrics

no code implementations11 Jun 2021 Saeid Asgari Taghanaki, Kristy Choi, Amir Khasahmadi, Anirudh Goyal

A fundamental challenge in artificial intelligence is learning useful representations of data that yield good performance on a downstream task, without overfitting to spurious input features.

Out-of-Distribution Generalization Representation Learning

Neural Network Compression for Noisy Storage Devices

no code implementations15 Feb 2021 Berivan Isik, Kristy Choi, Xin Zheng, Tsachy Weissman, Stefano Ermon, H. -S. Philip Wong, Armin Alaghi

Compression and efficient storage of neural network (NN) parameters is critical for applications that run on resource-constrained devices.

Neural Network Compression

Learning Task-Relevant Features via Contrastive Input Morphing

no code implementations1 Jan 2021 Saeid Asgari, Kristy Choi, Amir Hosein Khasahmadi, Anirudh Goyal

A fundamental challenge in artificial intelligence is learning useful representations of data that yield good performance on a downstream classification task, without overfitting to spurious input features.

Representation Learning

Encoding Musical Style with Transformer Autoencoders

no code implementations ICML 2020 Kristy Choi, Curtis Hawthorne, Ian Simon, Monica Dinculescu, Jesse Engel

We consider the problem of learning high-level controls over the global structure of generated sequences, particularly in the context of symbolic music generation with complex language models.

Music Generation

Fair Generative Modeling via Weak Supervision

1 code implementation ICML 2020 Kristy Choi, Aditya Grover, Trisha Singh, Rui Shu, Stefano Ermon

Real-world datasets are often biased with respect to key demographic factors such as race and gender.

Image Generation Test

Meta-Amortized Variational Inference and Learning

1 code implementation5 Feb 2019 Mike Wu, Kristy Choi, Noah Goodman, Stefano Ermon

Despite the recent success in probabilistic modeling and their applications, generative models trained using traditional inference techniques struggle to adapt to new distributions, even when the target distribution may be closely related to the ones seen during training.

Clustering Density Estimation +2

Neural Joint Source-Channel Coding

1 code implementation19 Nov 2018 Kristy Choi, Kedar Tatwawadi, Aditya Grover, Tsachy Weissman, Stefano Ermon

For reliable transmission across a noisy communication channel, classical results from information theory show that it is asymptotically optimal to separate out the source and channel coding processes.

NECST: Neural Joint Source-Channel Coding

no code implementations27 Sep 2018 Kristy Choi, Kedar Tatwawadi, Tsachy Weissman, Stefano Ermon

For reliable transmission across a noisy communication channel, classical results from information theory show that it is asymptotically optimal to separate out the source and channel coding processes.

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