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Neural Networks

11,300 papers

Papers per year

Papers

Team Kit Kittredge at SemEval-2019 Task 4: LSTM Voting System SEMEVAL 2019
Team Peter Brinkmann at SemEval-2019 Task 4: Detecting Biased News Articles Using Convolutional Neural Networks SEMEVAL 2019
Team Xenophilius Lovegood at SemEval-2019 Task 4: Hyperpartisanship Classification using Convolutional Neural Networks SEMEVAL 2019
UBC-NLP at SemEval-2019 Task 4: Hyperpartisan News Detection With Attention-Based Bi-LSTMs SEMEVAL 2019
CLEARumor at SemEval-2019 Task 7: ConvoLving ELMo Against Rumors SEMEVAL 2019
Lijunyi at SemEval-2019 Task 9: An attention-based LSTM and ensemble of different models for suggestion mining from online reviews and forums SEMEVAL 2019
NL-FIIT at SemEval-2019 Task 9: Neural Model Ensemble for Suggestion Mining SEMEVAL 2019
NTUA-ISLab at SemEval-2019 Task 9: Mining Suggestions in the wild SEMEVAL 2019
SSN-SPARKS at SemEval-2019 Task 9: Mining Suggestions from Online Reviews using Deep Learning Techniques on Augmented Data SEMEVAL 2019
WUT at SemEval-2019 Task 9: Domain-Adversarial Neural Networks for Domain Adaptation in Suggestion Mining SEMEVAL 2019
YNU_DYX at SemEval-2019 Task 9: A Stacked BiLSTM for Suggestion Mining Classification SEMEVAL 2019
ProblemSolver at SemEval-2019 Task 10: Sequence-to-Sequence Learning and Expression Trees SEMEVAL 2019
UNH at SemEval-2019 Task 12: Toponym Resolution in Scientific Papers SEMEVAL 2019
Expressive Priors in Bayesian Neural Networks: Kernel Combinations and Periodic Functions UAI 2019
The Incomplete Rosetta Stone problem: Identifiability results for Multi-view Nonlinear ICA UAI 2019
Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks UAI 2019
Efficient Neural Network Verification with Exactness Characterization UAI 2019
Adaptively Truncating Backpropagation Through Time to Control Gradient Bias UAI 2019
Noise Contrastive Priors for Functional Uncertainty UAI 2019
End-to-end Training of Deep Probabilistic CCA on Paired Biomedical Observations UAI 2019
Learnability for the Information Bottleneck UAI 2019
Block Neural Autoregressive Flow UAI 2019
ResNet with one-neuron hidden layers is a Universal Approximator NIPS 2018
How Many Samples are Needed to Estimate a Convolutional Neural Network? NIPS 2018
The streaming rollout of deep networks - towards fully model-parallel execution NIPS 2018