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Denoising Diffusion Probabilistic Models
We present high quality image synthesis results using diffusion probabil...
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Axial Attention in Multidimensional Transformers
We propose Axial Transformers, a self-attention-based autoregressive mod...
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Compression with Flows via Local Bits-Back Coding
Likelihood-based generative models are the backbones of lossless compres...
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Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent Variables
The bits-back argument suggests that latent variable models can be turne...
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Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design
Flow-based generative models are powerful exact likelihood models with e...
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Evolved Policy Gradients
We propose a meta-learning approach for learning gradient-based reinforc...
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One-Shot Imitation Learning
Imitation learning has been commonly applied to solve different tasks in...
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Evolution Strategies as a Scalable Alternative to Reinforcement Learning
We explore the use of Evolution Strategies (ES), a class of black box op...
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Generative Adversarial Imitation Learning
Consider learning a policy from example expert behavior, without interac...
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