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Christopher Tunnell
- ESANN 2023 - SOM-based Classification and a Novel Stopping Criterion for Astroparticle Applications [Details]
- ESANN 1995 - Analog Brownian weight movement for learning of artificial neural networks [Details]
- ESANN 2009 - Machine Learning with Labeled and Unlabeled Data [Details]
- ESANN 2010 - Introduction to Computational Intelligence Business Applications [Details]
- ESANN 2017 - Physical activity recognition from sub-bandage sensors using both feature selection and extraction [Details]
- ESANN 2004 - Architectures for Nanoelectronic Neural Networks: New Results [Details]
- ESANN 2016 - Enhancing a social science model-building workflow with interactive visualisation [Details]
- ESANN 1994 - Analysis of critical effects in a stochastic neural model [Details]
- ESANN 1995 - Invariant measure for an infinite neural network [Details]
- ESANN 2017 - TimeNet: Pre-trained deep recurrent neural network for time series classification [Details]
- ESANN 2024 - Automatic Miscalibration Diagnosis: Interpreting Probability Integral Transform (PIT) Histograms [Details]
- ESANN 2016 - Semantic Role Labelling for Robot Instructions using Echo State Networks [Details]
- ESANN 2016 - Active transfer learning for activity recognition [Details]
- ESANN 2018 - Anomaly detection in star light curves using hierarchical Gaussian processes [Details]
- ESANN 2018 - Efficient approximate representations for computationally expensive features [Details]
- ESANN 2018 - Person Identification and Discovery With Wrist Worn Accelerometer Data [Details]
- ESANN 2018 - A neural network cost function for highly class-imbalanced data sets [Details]
- ESANN 2008 - An FPGA-based model suitable for evolution and development of spiking neural networks [Details]