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Lars Carlsson
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2020 – today
- 2024
- [j34]Neda Haj-Hosseini
, Hanna Jonasson
Interactive remote electrical safety laboratory module in biomedical engineering education. Educ. Inf. Technol. 29(15): 20505-20521 (2024) - [j33]Staffan Arvidsson McShane, Ulf Norinder, Jonathan Alvarsson, Ernst Ahlberg, Lars Carlsson, Ola Spjuth:
CPSign: conformal prediction for cheminformatics modeling. J. Cheminformatics 16(1): 75 (2024) - 2023
- [c21]Simon Althoff, Johan Hallberg Szabadv'ary, Jonathan Anderson, Lars Carlsson:
Evaluation of conformal-based probabilistic forecasting methods for short-term wind speed forecasting. COPA 2023: 100-115 - [e3]Harris Papadopoulos, Khuong An Nguyen, Henrik Boström, Lars Carlsson:
Conformal and Probabilistic Prediction with Applications, 13-15 September 2023, Limassol, Cyprus. Proceedings of Machine Learning Research 204, PMLR 2023 [contents] - 2022
- [c20]Ulf Johansson, Henrik Boström, Khuong An Nguyen, Zhiyuan Luo, Lars Carlsson:
Preface. COPA 2022: 1-3 - [e2]Ulf Johansson, Henrik Boström, Khuong An Nguyen, Zhiyuan Luo, Lars Carlsson:
Conformal and Probabilistic Prediction with Applications, 24-26 August 2022, Brighton, UK. Proceedings of Machine Learning Research 179, PMLR 2022 [contents] - 2021
- [c19]Lars Carlsson, Zhiyuan Luo, Giovanni Cherubin, Khuong An Nguyen:
Preface. COPA 2021: 1-3 - [c18]Vladimir Vovk, Ivan Petej, Ilia Nouretdinov, Ernst Ahlberg, Lars Carlsson, Alex Gammerman:
Retrain or not retrain: conformal test martingales for change-point detection. COPA 2021: 191-210 - [c17]Hugo Werner, Lars Carlsson, Ernst Ahlberg, Henrik Boström:
Evaluation of updating strategies for conformal predictive systems in the presence of extreme events. COPA 2021: 229-242 - [e1]Lars Carlsson, Zhiyuan Luo, Giovanni Cherubin, Khuong An Nguyen:
Conformal and Probabilistic Prediction and Applications, 8-10 September 2021, Virtual Event. Proceedings of Machine Learning Research 152, PMLR 2021 [contents] - [i5]Vladimir Vovk, Ivan Petej, Ilia Nouretdinov, Ernst Ahlberg, Lars Carlsson, Alex Gammerman:
Retrain or not retrain: Conformal test martingales for change-point detection. CoRR abs/2102.10439 (2021) - [i4]Hannes Eriksson, Christos Dimitrakakis, Lars Carlsson:
High-dimensional near-optimal experiment design for drug discovery via Bayesian sparse sampling. CoRR abs/2104.11834 (2021) - 2020
- [c16]Vladimir Vovk, Ivan Petej, Paolo Toccaceli, Alexander Gammerman, Ernst Ahlberg, Lars Carlsson:
Conformal calibrators. COPA 2020: 84-99 - [c15]Hugo Werner, Lars Carlsson, Ernst Ahlberg, Henrik Boström:
Evaluating different approaches to calibrating conformal predictive systems. COPA 2020: 134-150
2010 – 2019
- 2019
- [j32]Noé Sturm
Application of Bioactivity Profile-Based Fingerprints for Building Machine Learning Models. J. Chem. Inf. Model. 59(3): 962-972 (2019) - [j31]Rubén Buendía, Thierry Kogej, Ola Engkvist
Accurate Hit Estimation for Iterative Screening Using Venn-ABERS Predictors. J. Chem. Inf. Model. 59(3): 1230-1237 (2019) - [j30]Alexander Gammerman
Conformal and probabilistic prediction with applications: editorial. Mach. Learn. 108(3): 379-380 (2019) - [c14]Jiangming Sun, Nina Jeliazkova, Vladimir I. Chupakhin, José Felipe Golib Dzib, Lars Carlsson, Jörg K. Wegner, Hugo Ceulemans, Ivan Georgiev, Vedrin Jeliazkov, Nikolay T. Kochev, Thomas J. Ashby, Hongming Chen:
ExCAPE-DB: An Integrated Large Scale Dataset Facilitating Big Data Analysis in Chemogenomics. BNAIC/BENELEARN 2019 - [c13]Ola Spjuth, Robin Carrión Brännström, Lars Carlsson, Niharika Gauraha:
Combining Prediction Intervals on Multi-Source Non-Disclosed Regression Datasets. COPA 2019: 53-65 - [i3]Ola Spjuth, Robin Carrión Brännström, Lars Carlsson, Niharika Gauraha:
Combining Prediction Intervals on Multi-Source Non-Disclosed Regression Datasets. CoRR abs/1908.05571 (2019) - 2018
- [j29]Fredrik Svensson
Conformal Regression for Quantitative Structure-Activity Relationship Modeling - Quantifying Prediction Uncertainty. J. Chem. Inf. Model. 58(5): 1132-1140 (2018) - [c12]Ernst Ahlberg, Rubén Buendía, Lars Carlsson:
Using Venn-Abers predictors to assess cardio-vascular risk. COPA 2018: 132-146 - [c11]Niharika Gauraha, Lars Carlsson, Ola Spjuth:
Conformal prediction in learning under privileged information paradigm with applications in drug discovery. COPA 2018: 147-156 - [c10]Rubén Buendía, Ola Engkvist, Lars Carlsson, Thierry Kogej, Ernst Ahlberg:
Venn-Abers predictors for improved compound iterative screening in drug discovery. COPA 2018: 201-219 - [i2]Niharika Gauraha, Lars Carlsson, Ola Spjuth:
Conformal Prediction in Learning Under Privileged Information Paradigm with Applications in Drug Discovery. CoRR abs/1803.11136 (2018) - [i1]Ola Spjuth, Lars Carlsson, Niharika Gauraha:
Aggregating Predictions on Multiple Non-disclosed Datasets using Conformal Prediction. CoRR abs/1806.04000 (2018) - 2017
- [j28]Ernst Ahlberg
Current application of conformal prediction in drug discovery - Two useful applications. Ann. Math. Artif. Intell. 81(1-2): 145-154 (2017) - [j27]Claus Bendtsen
Improving machine learning in early drug discovery. Ann. Math. Artif. Intell. 81(1-2): 155-166 (2017) - [j26]Jiangming Sun, Nina Jeliazkova
ExCAPE-DB: an integrated large scale dataset facilitating Big Data analysis in chemogenomics. J. Cheminformatics 9(1): 17:1-17:9 (2017) - [j25]Egon L. Willighagen
The Chemistry Development Kit (CDK) v2.0: atom typing, depiction, molecular formulas, and substructure searching. J. Cheminformatics 9(1): 33:1-33:19 (2017) - [j24]Jiangming Sun, Nina Jeliazkova, Vladimir I. Chupakhin, José Felipe Golib Dzib, Ola Engkvist
Erratum to: ExCAPE-DB: an integrated large scale dataset facilitating Big Data analysis in chemogenomics. J. Cheminformatics 9(1): 41:1 (2017) - [j23]Egon L. Willighagen
Erratum to: The Chemistry Development Kit (CDK) v2.0: atom typing, depiction, molecular formulas, and substructure searching. J. Cheminformatics 9(1): 53 (2017) - [j22]Jiangming Sun
Applying Mondrian Cross-Conformal Prediction To Estimate Prediction Confidence on Large Imbalanced Bioactivity Data Sets. J. Chem. Inf. Model. 57(7): 1591-1598 (2017) - [c9]Staffan Arvidsson, Ola Spjuth, Lars Carlsson, Paolo Toccaceli:
Prediction of Metabolic Transformations using Cross Venn-ABERS Predictors. COPA 2017: 118-131 - [c8]Ernst Ahlberg, Susanne Winiwarter, Henrik Boström, Henrik Linusson, Tuve Löfström, Ulf Norinder, Ulf Johansson, Ola Engkvist, Oscar Hammar, Claus Bendtsen, Lars Carlsson:
Using Conformal Prediction to Prioritize Compound Synthesis in Drug Discovery. COPA 2017: 174-184 - [c7]Lars Carlsson, Claus Bendtsen, Ernst Ahlberg:
Comparing Performance of Different Inductive and Transductive Conformal Predictors Relevant to Drug Discovery. COPA 2017: 201-212 - 2015
- [j21]Martin Eklund, Ulf Norinder
The application of conformal prediction to the drug discovery process. Ann. Math. Artif. Intell. 74(1-2): 117-132 (2015) - [j20]Behrooz Torabi Moghadam, Jonathan Alvarsson
Scaling Predictive Modeling in Drug Development with Cloud Computing. J. Chem. Inf. Model. 55(1): 19-25 (2015) - [c6]Marco Capuccini
Conformal Prediction in Spark: Large-Scale Machine Learning with Confidence. BDC 2015: 61-67 - [c5]Lars Carlsson, Ernst Ahlberg, Henrik Boström, Ulf Johansson, Henrik Linusson:
Modifications to p-Values of Conformal Predictors. SLDS 2015: 251-259 - [c4]Ulf Johansson, Ernst Ahlberg, Henrik Boström, Lars Carlsson, Henrik Linusson, Cecilia Sönströd:
Handling Small Calibration Sets in Mondrian Inductive Conformal Regressors. SLDS 2015: 271-280 - [c3]Ernst Ahlberg, Ola Spjuth
Interpretation of Conformal Prediction Classification Models. SLDS 2015: 323-334 - 2014
- [j19]Marko Toplak
Assessment of Machine Learning Reliability Methods for Quantifying the Applicability Domain of QSAR Regression Models. J. Chem. Inf. Model. 54(2): 431-441 (2014) - [j18]Martin Eklund, Ulf Norinder
Choosing Feature Selection and Learning Algorithms in QSAR. J. Chem. Inf. Model. 54(3): 837-843 (2014) - [j17]Mats Eriksson, Hongming Chen, Lars Carlsson, J. Willem M. Nissink
Beyond the Scope of Free-Wilson Analysis. 2 Can Distance Encoded R-Group Fingerprints Provide Interpretable Nonlinear Models? J. Chem. Inf. Model. 54(4): 1117-1128 (2014) - [j16]Ulf Norinder
Introducing Conformal Prediction in Predictive Modeling. A Transparent and Flexible Alternative to Applicability Domain Determination. J. Chem. Inf. Model. 54(6): 1596-1603 (2014) - [j15]Jonathan Alvarsson
Ligand-Based Target Prediction with Signature Fingerprints. J. Chem. Inf. Model. 54(10): 2647-2653 (2014) - [j14]Ernst Ahlberg Helgee, Lars Carlsson, Scott Boyer:
Computational Derivation of Structural Alerts from Large Toxicology Data Sets. J. Chem. Inf. Model. 54(10): 2945-2952 (2014) - [j13]Jonathan Alvarsson
Benchmarking Study of Parameter Variation When Using Signature Fingerprints Together with Support Vector Machines. J. Chem. Inf. Model. 54(11): 3211-3217 (2014) - [c2]Lars Carlsson, Martin Eklund, Ulf Norinder
Aggregated Conformal Prediction. AIAI Workshops 2014: 231-240 - 2013
- [j12]Ola Spjuth
Bioclipse-R: integrating management and visualization of life science data with statistical analysis. Bioinform. 29(2): 286-289 (2013) - [j11]David J. Wood, Lars Carlsson, Martin Eklund, Ulf Norinder
QSAR with experimental and predictive distributions: an information theoretic approach for assessing model quality. J. Comput. Aided Mol. Des. 27(3): 203-219 (2013) - [j10]Pablo Carbonell
Stereo Signature Molecular Descriptor. J. Chem. Inf. Model. 53(4): 887-897 (2013) - [j9]Hongming Chen, Lars Carlsson, Mats Eriksson, Péter L. Várkonyi, Ulf Norinder
Beyond the Scope of Free-Wilson Analysis: Building Interpretable QSAR Models with Machine Learning Algorithms. J. Chem. Inf. Model. 53(6): 1324-1336 (2013) - [j8]Jonna C. Stålring, Pedro Almeida, Lars Carlsson, Ernst Ahlberg Helgee, Catrin Hasselgren Arnby, Scott Boyer:
Localized Heuristic Inverse Quantitative Structure Activity Relationship with Bulk Descriptors Using Numerical Gradients. J. Chem. Inf. Model. 53(8): 2001-2017 (2013) - 2012
- [c1]Martin Eklund, Ulf Norinder
Application of Conformal Prediction in QSAR. AIAI (2) 2012: 166-175 - 2011
- [j7]Jonna C. Stålring, Lars Carlsson, Pedro Almeida, Scott Boyer:
AZOrange - High performance open source machine learning for QSAR modeling in a graphical programming environment. J. Cheminformatics 3: 28 (2011) - [j6]Ola Spjuth
Integrated Decision Support for Assessing Chemical Liabilities. J. Chem. Inf. Model. 51(8): 1840-1847 (2011) - 2010
- [j5]Lars Carlsson, Ola Spjuth
Use of historic metabolic biotransformation data as a means of anticipating metabolic sites using MetaPrint2D and Bioclipse. BMC Bioinform. 11: 362 (2010) - [j4]Ernst Ahlberg Helgee, Lars Carlsson, Scott Boyer, Ulf Norinder
Evaluation of Quantitative Structure-Activity Relationship Modeling Strategies: Local and Global Models. J. Chem. Inf. Model. 50(4): 677-689 (2010)
2000 – 2009
- 2009
- [j3]Lars Carlsson, Ernst Ahlberg Helgee, Scott Boyer:
Interpretation of Nonlinear QSAR Models Applied to Ames Mutagenicity Data. J. Chem. Inf. Model. 49(11): 2551-2558 (2009) - [j2]Ernst Ahlberg Helgee, Lars Carlsson, Scott Boyer:
A Method for Automated Molecular Optimization Applied to Ames Mutagenicity Data. J. Chem. Inf. Model. 49(11): 2559-2563 (2009) - 2007
- [j1]Scott Boyer, Catrin Hasselgren Arnby, Lars Carlsson, James Smith
Reaction Site Mapping of Xenobiotic Biotransformations. J. Chem. Inf. Model. 47(2): 583-590 (2007)
Coauthor Index
Ernst Ahlberg Helgee
aka: Ernst Ahlberg
aka: Ernst Ahlberg
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