Instruct: Given a paper title, retrieve paper titles that are cited by the given paper.
Query: Deep Convolutional Networks as shallow Gaussian Processes
Deep Gaussian Processes with Convolutional Kernels
Learning the Structure of Deep Convolutional Networks
Integrating Gaussian mixtures into deep neural networks: Softmax layer with hidden variables
Flexible and efficient Gaussian process models for machine learning
Thoughts on Massively Scalable Gaussian Processes
The Deep Regression Bayesian Network and Its Applications: Probabilistic Deep Learning for Computer Vision
Optimization Landscape and Expressivity of Deep CNNs
The Shallow End: Empowering Shallower Deep-Convolutional Networks through Auxiliary Outputs
A unifying view of sparse approximate Gaussian process regression
Learning Gaussian processes from multiple tasks
A Gaussian Mixture Model layer jointly optimized with discriminative features within a Deep Neural Network architecture
Model Learning with Local Gaussian Process Regression
Warped Gaussian Processes
Stochastic Back-propagation and Variational Inference in Deep Latent Gaussian Models
Training Deeper Convolutional Networks with Deep Supervision
Dependent Gaussian Processes
Greedy Layer-Wise Training of Deep Networks
Gaussian Processes Over Graphs
Deep Gaussian Processes for Regression using Approximate Expectation Propagation
Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences
Characteristic distribution of finite-time Lyapunov exponents for chimera states
Laparoscopic Radical Nephrectomy and Inferior Vena Cava Thrombectomy in the Treatment of Renal Cell Carcinoma
Use of Additive Waxup and Direct Intraoral Mock-up for Enamel Preservation with
Authorship attribution with thousands of candidate authors
Convolutional Gaussian Processes