Neural Network Baseline

Neural network baselines serve as crucial points of comparison in evaluating the performance of novel machine learning models across diverse applications. Research currently focuses on developing and improving these baselines, encompassing various architectures like convolutional neural networks (CNNs), transformers, and spiking neural networks (SNNs), often tailored to specific data types (e.g., images, time series, graphs). The establishment of robust and efficient baselines is essential for rigorous model evaluation, facilitating advancements in fields ranging from medical diagnosis and industrial process monitoring to natural language processing and computer vision. Improved baselines also help to identify limitations in existing approaches and guide the development of more effective and interpretable models.

Papers

January 27, 2023

PrecTime: A Deep Learning Architecture for Precise Time Series Segmentation in Industrial Manufacturing Operations
Stefan Gaugel, Manfred Reichert
Deep Learning Architecture Neural Network Baseline Object State Industrial Process Temporal Neural Network Time Series Segmentation

December 1, 2022

Deep Kernel Learning for Mortality Prediction in the Face of Temporal Shift
Miguel Rios, Ameen Abu-Hanna
Human Face Neural Model Prediction Uncertainty Temporal Shift Neural Network Baseline Mortality Prediction Overconfident Prediction Deep Kernel Learning

October 26, 2022

TuneUp: A Simple Improved Training Strategy for Graph Neural Networks
Weihua Hu, Kaidi Cao, Kexin Huang, Edward W Huang, Karthik Subbian, Kenji Kawaguchi, Jure Leskovec
Graph Neural Network Gene Level GNN GNN Architecture Neural Network Baseline Training Strategy

October 20, 2022

Robustcaps: a transformation-robust capsule network for image classification
Sai Raam Venkataraman, S. Balasubramanian, R. Raghunatha Sarma
Image Classification Capsule Network Neural Network Baseline Transformation Robustness

October 12, 2022

S4ND: Modeling Images and Videos as Multidimensional Signals Using State Spaces
Eric Nguyen, Karan Goel, Albert Gu, Gordon W. Downs, Preey Shah, Tri Dao, Stephen A. Baccus, Christopher Ré
Gameplay Video State Space Image Modeling Convolutional Kernel Neural Network Baseline Multivariate Signal

September 20, 2022

Feature embedding in click-through rate prediction
Samo Pahor, Davorin Kopič, Jure Demšar
Matrix Factorization Click Through Rate Prediction Content Based Feature Augmented Data Neural Network Baseline

September 16, 2022

Confidence-Guided Data Augmentation for Improved Semi-Supervised Training
Fadoua Khmaissia, Hichem Frigui
Data Augmentation Image Classification Variational Autoencoder Synthetic Image Neural Network Baseline Semi Supervised Training Garment Synthesis

September 10, 2022

Deep Baseline Network for Time Series Modeling and Anomaly Detection
Cheng Ge, Xi Chen, Ming Wang, Jin Wang
Deep Learning Anomaly Detection Time Series Deep Network Neural Network Baseline

September 7, 2022

Multimodal Speech Enhancement Using Burst Propagation
Mohsin Raza, Leandro A. Passos, Ahmed Khubaib, Ahsan Adeel
Neural Network Baseline Visual Stimulus Audio Visual Speech Enhancement Kernel Aware Burst

August 26, 2022

Multi tasks RetinaNet for mitosis detection
Chen Yang, Wang Ziyue, Fang Zijie, Bian Hao, Zhang Yongbing
Deep Learning Multi Task Classification Task Neural Network Baseline Mitosis Detection

August 24, 2022

Next-Year Bankruptcy Prediction from Textual Data: Benchmark and Baselines
Henri Arno, Klaas Mulier, Joke Baeck, Thomas Demeester
New Benchmark Baseline Result Benchmark Datasets Unstructured Data Bag of Word Neural Network Baseline Bankruptcy Prediction

July 19, 2022

HSE-NN Team at the 4th ABAW Competition: Multi-task Emotion Recognition and Learning from Synthetic Images
Andrey V. Savchenko
LeArning Abstract Multi Task Learning Emotion Recognition Synthetic Image Neural Network Baseline Behavior Analysis in the Wild

May 18, 2022

Empirical Advocacy of Bio-inspired Models for Robust Image Recognition
Harshitha Machiraju, Oh-Hyeon Choung, Michael H. Herzog, Pascal Frossard
Deep Convolutional Neural Network Adversarial Perturbation Bio Inspired Neural Network Baseline Robust Recognition

December 16, 2021

Spatio-Temporal CNN baseline method for the Sports Video Task of MediaEval 2021 benchmark
Pierre-Etienne Martin
New Benchmark Detection Task Neural Network Baseline Stroke Detection Sport Video Byzantine Seal

December 15, 2021

Ensuring DNN Solution Feasibility for Optimization Problems with Convex Constraints and Its Application to DC Optimal Power Flow Problems
Tianyu Zhao, Xiang Pan, Minghua Chen, Steven H. Low
Neural Network Application Proficiency Optimization Problem Constrained Optimization Optimal Power Flow Neural Network Baseline Deep Neural Network Training Convex Constraint

December 10, 2021

LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks
Adam Goodge, Bryan Hooi, See Kiong Ng, Wee Siong Ng
Graph Neural Network Anomaly Detection Neural Network Baseline Deep Learning Based Anomaly Detection