Pipa, Gordon
Full Name
Pipa, Gordon
Variants
Pipa, G
Pipa, Gordon
Pipa, Gordon
Main Affiliation
FIS NetID
ORCID
Country
Germany
Lädt ...
2
0
20
0
false
Lädt ...
3
0
20
0
false
61-80 von 91
Erscheinungsdatum | Titel | Autor(en) | |
---|---|---|---|
61 | 2019 | A Bayesian Monte Carlo approach for predicting the spread of infectious diseases | Stojanović, Olivera; Leugering, Johannes; Pipa, Gordon ; Ghozzi, Stéphane; Ullrich, Alexander |
62 | 2019 | Human Decisions in Moral Dilemmas are Largely Described by Utilitarianism: Virtual Car Driving Study Provides Guidelines for Autonomous Driving Vehicles | Faulhaber, Anja K.; Dittmer, Anke; Blind, Felix; Waechter, Maximilian A.; Timm, Silja; Suetfeld, Leon R.; Stephan, Achim ; Pipa, Gordon ; Koenig, Peter |
63 | 2019 | A Bayesian Monte Carlo approach for predicting the spread of infectious diseases | Stojanovic, Olivera; Leugering, Johannes; Pipa, Gordon ; Ghozzi, Stephane; Ullrich, Alexander |
64 | 2019 | How does the method change what we measure? Comparing virtual reality and text-based surveys for the assessment of moral decisions in traffic dilemmas | Suetfeld, Leon Rene; Ehinger, V, Benedikt; Koenig, Peter ; Pipa, Gordon |
65 | 2019 | Moral Judgements on the Actions of Self-Driving Cars and Human Drivers in Dilemma Situations From Different Perspectives | Kallioinen, N.; Pershina, M.; Zeiser, J.; Nosrat Nezami, F.; Pipa, G. ; Stephan, A. ; König, P. |
66 | 2019 | Bistable Perception in Conceptor Networks | Meyer zu Driehausen, F.; Busche, R.; Leugering, J.; Pipa, G. |
67 | 2019 | Combining Deep Learning and (Structural) Feature-Based Classification Methods for Copyright-Protected PDF Documents | Garita Figueiredo, R.; Kühnberger, K.-U. ; Pipa, G. ; Thelen, T. |
68 | 2020 | Reliability and comparability of human brain structural covariance networks | Carmon, Jona; Heege, Jil; Necus, Joe H.; Owen, Thomas W.; Pipa, Gordon ; Kaiser, Marcus; Taylor, Peter N.; Wang, Yujiang |
69 | 2020 | Real-Time Dialogue between Experimenters and Dreamers During REM Sleep | Konkoly, Karen; Appel, Kristoffer ; Chabani, Emma; Mironov, Alexander Y.; Mangiaruga, Anastasia; Gott, Jarrod; Mallett, Remington; Caughran, Bruce; Witkowski, Sarah; Whitmore, Nathan; Berent, Jonathan B.; Weber, Frederik D.; Pipa, Gordon ; Türker, Başak; Maranci, Jean-Baptiste; Sinin, Artyom; Dorokhov, Vladimir B.; Arnulf, Isabelle; Oudiette, Delphine; Dresler, Martin; Paller, Ken A. |
70 | 2020 | Adaptive Blending Units: Trainable Activation Functions for Deep Neural Networks | Sütfeld, Leon René; Brieger, Flemming; Finger, Holger; Füllhase, Sonja; Pipa, Gordon |
71 | 2020 | Predicting epileptic seizures using nonnegative matrix factorization | Stojanovic, Olivera; Kuhlmann, Levin; Pipa, Gordon |
72 | 2020 | Project Westdrive: Unity City With Self-Driving Cars and Pedestrians for Virtual Reality Studies | Nezami, F.N.; Wächter, M.A.; Pipa, G. ; König, P. |
73 | 2021 | Real-time dialogue between experimenters and dreamers during REM sleep | Konkoly, Karen R.; Appel, Kristoffer ; Chabani, Emma; Mangiaruga, Anastasia; Gott, Jarrod; Mallett, Remington; Caughran, Bruce; Witkowski, Sarah; Whitmore, Nathan W.; Mazurek, Christopher Y.; Berent, Jonathan B.; Weber, Frederik D.; Turker, Basxak; Leu-Semenescu, Smaranda; Maranci, Jean-Baptiste; Pipa, Gordon ; Arnulf, Isabelle; Oudiette, Delphine; Dresler, Martin; Paller, Ken A. |
74 | 2021 | Is Deep-Learning and Natural Language Processing Transcending the Financial Forecasting? Investigation Through Lens of News Analytic Process | Khalil, Faisal; Pipa, Gordon |
75 | 2021 | Bayesian hierarchical models can infer interpretable predictions of leaf area index from heterogeneous datasets | Stojanović, Olivera; Siegmann, Bastian; Jarmer, Thomas ; Pipa, Gordon ; Leugering, Johannes |
76 | 2021 | A trajectory-based loss function to learn missing terms in bifurcating dynamical systems | Vortmeyer-Kley, Rahel; Nieters, Pascal ; Pipa, Gordon |
77 | 2021 | A Minimal Model of Neural Computation with Dendritic Plateau Potentials | Leugering, Johannes; Nieters, Pascal ; Pipa, Gordon |
78 | 2021 | Learning sparse and meaningful representations through embodiment | Clay, Viviane; Koenig, Peter ; Kuehnberger, Kai-Uwe ; Pipa, Gordon |
79 | 2021 | Biologically Inspired Deep Learning Model for Efficient Foveal-Peripheral Vision | Lukanov, Hristofor; Koenig, Peter ; Pipa, Gordon |
80 | 2021 | Westdrive X LoopAR: An Open-Access Virtual Reality Project in Unity for Evaluating User Interaction Methods during Takeover Requests | Nezami, Farbod N.; Waechter, Maximilian A.; Maleki, Nora; Spaniol, Philipp; Kuehne, Lea M.; Haas, Anke; Pingel, Johannes M.; Tiemann, Linus; Nienhaus, Frederik; Keller, Lynn; Koenig, Sabine U.; Koenig, Peter ; Pipa, Gordon |