conftrace_

uncertainty estimation

648 papers

Explore in graph

Also known as

UE

Co-occurring keywords

uncertainty quantification (1393) out-of-distribution detection (617) large language model (13587) bayesian inference (1907) active learning (1301) neural network (6616) semantic segmentation (3186) variational inference (2069) semi-supervised learning (2341) domain adaptation (4595)

Papers

Uncertainty-Guided Model Generalization to Unseen Domains CVPR 2021
Capturing Uncertainty in Unsupervised GPS Trajectory Segmentation Using Bayesian Deep Learning AAAI 2021
Exploiting Sample Uncertainty for Domain Adaptive Person Re-Identification AAAI 2021
On the Calibration and Uncertainty of Neural Learning to Rank Models for Conversational Search EACL 2021
Measuring and Improving Model-Moderator Collaboration using Uncertainty Estimation IJCNLP 2021
Active Speaker Detection as a Multi-Objective Optimization with Uncertainty-Based Multimodal Fusion INTERSPEECH 2021
Fusing the Old with the New: Learning Relative Camera Pose with Geometry-Guided Uncertainty CVPR 2021
UASNet: Uncertainty Adaptive Sampling Network for Deep Stereo Matching ICCV 2021
Uncertainty-Aware Multi-View Representation Learning AAAI 2021
Uncertainty-Aware Camera Pose Estimation From Points and Lines CVPR 2021
Improved Image Matting via Real-Time User Clicks and Uncertainty Estimation CVPR 2021
Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning ICML 2021
Self-Training Sampling with Monolingual Data Uncertainty for Neural Machine Translation IJCNLP 2021
Masksembles for Uncertainty Estimation CVPR 2021
Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble NIPS 2021
Vector Quantized Bayesian Neural Network Inference for Data Streams AAAI 2021
Active Learning for Lane Detection: A Knowledge Distillation Approach ICCV 2021
Uncertainty-Aware Multi-Shot Knowledge Distillation for Image-Based Object Re-Identification AAAI 2020
NGBoost: Natural Gradient Boosting for Probabilistic Prediction ICML 2020
Influenza Forecasting Framework based on Gaussian Processes ICML 2020
Towards Maximizing the Representation Gap between In-Domain & Out-of-Distribution Examples NIPS 2020
Non-Parametric Calibration for Classification AISTATS 2020
Uncertainty-Aware Learning for Zero-Shot Semantic Segmentation NIPS 2020
Understanding and Exploring the Network with Stochastic Architectures NIPS 2020
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts NIPS 2020