Advances in reinforcement learning (RL) often rely on massive compute
re...
Dealing with incomplete information is a well studied problem in the con...
In this paper we introduce the temporally factorized 3D convolution (3TC...
This paper introduces the Indian Chefs Process (ICP), a Bayesian
nonpara...
Perceived personality traits attributed to an individual do not have to
...
3D convolutional neural networks are difficult to train because they are...
Generative adversarial networks (GANs) are the state of the art in gener...
Particle-based variational inference offers a flexible way of approximat...
In this paper, we introduce a new form of amortized variational inferenc...
This paper introduces Wasserstein variational inference, a new form of
a...
Personality analysis has been widely studied in psychology, neuropsychol...
Explainability and interpretability are two critical aspects of decision...
This paper introduces the kernel mixture network, a new method for
nonpa...
Here, we present a novel approach to solve the problem of reconstructing...
Recent years have seen a sharp increase in the number of related yet dis...
Estimating the state of a dynamical system from a series of noise-corrup...
Here, we develop an audiovisual deep residual network for multimodal app...
In this paper, we use deep neural networks for inverting face sketches t...