activity
20182022
most citedU-Net: Going Deeper with Nested U-Structure for Salient Object Detection

2.4k citations · 2.5k across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2022★ 4 cited

A Simple Decentralized Cross-Entropy Method

Zichen Zhang, Jun Jin, Martin Jagersand +2

Cross-Entropy Method (CEM) is commonly used for planning in model-based reinforcement learning (MBRL) where a centralized approach is typically utilized to update the sampling dist…

cs.LG2022

Managing Temporal Resolution in Continuous Value Estimation: A Fundamental Trade-off

Zichen Zhang, Johannes Kirschner, Junxi Zhang +4

A default assumption in reinforcement learning (RL) and optimal control is that observations arrive at discrete time points on a fixed clock cycle. Yet, many applications involve c…

cs.CV2021★ 2 cited

Sample Efficient Learning of Image-Based Diagnostic Classifiers Using Probabilistic Labels

Roberto Vega, Pouneh Gorji, Zichen Zhang +5

Deep learning approaches often require huge datasets to achieve good generalization. This complicates its use in tasks like image-based medical diagnosis, where the small training…

cs.CV2020★ 2.4k cited

U-Net: Going Deeper with Nested U-Structure for Salient Object Detection

Xuebin Qin, Zichen Zhang, Chenyang Huang +3

In this paper, we design a simple yet powerful deep network architecture, U-Net, for salient object detection (SOD). The architecture of our U-Net is a two-level nested U-s…

cs.LG2019★ 3 cited

Reducing Selection Bias in Counterfactual Reasoning for Individual Treatment Effects Estimation

Zichen Zhang, Qingfeng Lan, Lei Ding +3

Counterfactual reasoning is an important paradigm applicable in many fields, such as healthcare, economics, and education. In this work, we propose a novel method to address the is…

cs.RO2018★ 18 cited

Robot eye-hand coordination learning by watching human demonstrations: a task function approximation approach

Jun Jin, Laura Petrich, Masood Dehghan +2

We present a robot eye-hand coordination learning method that can directly learn visual task specification by watching human demonstrations. Task specification is represented as a…