research
∙
05/18/2023
Bayesian Reparameterization of Reward-Conditioned Reinforcement Learning with Energy-based Models
Recently, reward-conditioned reinforcement learning (RCRL) has gained po...
share
research
∙
11/14/2022
SPE: Symmetrical Prompt Enhancement for Fact Probing
Pretrained language models (PLMs) have been shown to accumulate factual ...
research
∙
10/31/2022
Guided Conditional Diffusion for Controllable Traffic Simulation
Controllable and realistic traffic simulation is critical for developing...
research
∙
10/11/2022
Robust and Controllable Object-Centric Learning through Energy-based Models
Humans are remarkably good at understanding and reasoning about complex ...
research
∙
06/26/2022
Your Autoregressive Generative Model Can be Better If You Treat It as an Energy-Based One
Autoregressive generative models are commonly used, especially for those...
research
∙
07/27/2021
Energy-Based Open-World Uncertainty Modeling for Confidence Calibration
Confidence calibration is of great importance to the reliability of deci...
research
∙
07/13/2020
AUTO3D: Novel view synthesis through unsupervisely learned variational viewpoint and global 3D representation
This paper targets on learning-based novel view synthesis from a single ...
research
∙
06/23/2020
Rethinking Distributional Matching Based Domain Adaptation
Domain adaptation (DA) is a technique that transfers predictive models t...
research
∙
03/12/2020
Your GAN is Secretly an Energy-based Model and You Should use Discriminator Driven Latent Sampling
We show that the sum of the implicit generator log-density log p_g of a ...
research
∙
11/18/2019
Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models
AI Safety is a major concern in many deep learning applications such as ...
research
∙
11/03/2019
Conservative Wasserstein Training for Pose Estimation
This paper targets the task with discrete and periodic class labels (e.g...
research
∙
10/13/2017
Residual Connections Encourage Iterative Inference
Residual networks (Resnets) have become a prominent architecture in deep...
research
∙
02/27/2017
Boundary-Seeking Generative Adversarial Networks
We introduce a novel approach to training generative adversarial network...
research
∙
02/26/2017
Maximum-Likelihood Augmented Discrete Generative Adversarial Networks
Despite the successes in capturing continuous distributions, the applica...
research
∙
12/07/2016
Mode Regularized Generative Adversarial Networks
Although Generative Adversarial Networks achieve state-of-the-art result...
research
∙
02/26/2016