496 citations · 746 across the 4 of their papers we have counts for
4 papers
M-Net: Integrating Spectral Features and Physical Field Operators into Deep Learning for Medical Image Segmentation
Jing Zhu, Ye Wang, Fumin Wang
Purpose: Deep learning-based medical image segmentation has achieved remarkable success, yet purely data-driven approaches often fail to exploit the rich mathematical structure inh…
Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards
Mel Vecerik, Todd Hester, Jonathan Scholz +7
We propose a general and model-free approach for Reinforcement Learning (RL) on real robotics with sparse rewards. We build upon the Deep Deterministic Policy Gradient (DDPG) algor…
Grounded Language Learning in a Simulated 3D World
Karl Moritz Hermann, Felix Hill, Simon Green +11
We are increasingly surrounded by artificially intelligent technology that takes decisions and executes actions on our behalf. This creates a pressing need for general means to com…
Latent Predictor Networks for Code Generation
Wang Ling, Edward Grefenstette, Karl Moritz Hermann +4
Many language generation tasks require the production of text conditioned on both structured and unstructured inputs. We present a novel neural network architecture which generates…