213 results on '"Marc Peter Deisenroth"'
Search Results
102. Gaussian Processes for Data-Efficient Learning in Robotics and Control.
103. Feedback error learning for rhythmic motor primitives.
104. Model-based imitation learning by probabilistic trajectory matching.
105. Data-Efficient Generalization of Robot Skills with Contextual Policy Search.
106. Learning Deep Belief Networks from Non-stationary Streams.
107. Toward fast policy search for learning legged locomotion.
108. Expectation Propagation in Gaussian Process Dynamical Systems.
109. A general perspective on Gaussian filtering and smoothing: Explaining current and deriving new algorithms.
110. PILCO: A Model-Based and Data-Efficient Approach to Policy Search.
111. Gambit: An autonomous chess-playing robotic system.
112. Neural Embeddings of Graphs in Hyperbolic Space.
113. Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control.
114. The reparameterization trick for acquisition functions.
115. A Brief Survey of Deep Reinforcement Learning.
116. Customer Life Time Value Prediction Using Embeddings.
117. Analytic moment-based Gaussian process filtering.
118. Probabilistic Inference for Fast Learning in Control.
119. Approximate dynamic programming with Gaussian processes.
120. Model-Based Reinforcement Learning with Continuous States and Actions.
121. Finite-Horizon Optimal State-Feedback Control of Nonlinear Stochastic Systems Based on a Minimum Principle.
122. Social and Affective Robotics Tutorial.
123. A Survey on Policy Search for Robotics.
124. Probabilistic model-based imitation learning.
125. Probabilistic movement modeling for intention inference in human-robot interaction.
126. Detecting the Age of Twitter Users.
127. Real-Time Association Mining in Large Social Networks.
128. Robust Filtering and Smoothing with Gaussian Processes.
129. State-Space Inference and Learning with Gaussian Processes.
130. Gaussian process dynamic programming.
131. Data-Efficient Learning of Feedback Policies from Image Pixels using Deep Dynamical Models.
132. Bayesian Optimization with Dimension Scheduling: Application to Biological Systems.
133. From Pixels to Torques: Policy Learning with Deep Dynamical Models.
134. Probabilistic Modeling of Human Movements for Intention Inference.
135. Preface.
136. Learning to Control a Low-Cost Manipulator using Data-Efficient Reinforcement Learning.
137. Manifold Gaussian Processes for Regression.
138. Learning deep dynamical models from image pixels.
139. Hierarchical Mixture-of-Experts Model for Large-Scale Gaussian Process Regression.
140. High-dimensional Bayesian optimization with projections using quantile Gaussian processes
141. Multi-Task Policy Search.
142. A Probabilistic Perspective on Gaussian Filtering and Smoothing
143. When Models Meet Data
144. Mathematics for Machine Learning
145. Gaussian Process Domain Experts for Modeling of Facial Affect
146. Accelerating the BSM interpretation of LHC data with machine learning
147. High-dimensional Bayesian optimization using low-dimensional feature spaces
148. Bayesian Multiobjective Optimisation With Mixed Analytical and Black-Box Functions: Application to Tissue Engineering
149. Design of Experiments for Model Discrimination using Gaussian Process Surrogate Models
150. GPdoemd: a Python package for design of experiments for model discrimination
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