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ORCIDFilipe Rodrigues 0001
Person information
- affiliation: Technical University of Denmark, Department of Management Engineering, Kongens Lyngby, Denmark
- affiliation: University of Coimbra, CISUC, Portugal
Other persons with the same name
- Filipe Rodrigues — disambiguation page
- Filipe Rodrigues 0002
![[0000-0002-3770-5456]](https://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-3770-5456")
— University of Aveiro, Department of Mathematics, Portugal
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Journal Articles
- 2024
[j19]Zhongcan Li, Ping Huang, Chao Wen, Wei Dong, Yindong Ji, Filipe Rodrigues:
Railway network delay evolution: A heterogeneous graph neural network approach. Appl. Soft Comput. 159: 111640 (2024)- 2023
- [j18]Zhongcan Li, Ping Huang, Chao Wen, Jie Li, Filipe Rodrigues:
Prediction of departure delays at original stations using deep learning approaches: A combination of route conflicts and rolling stock connections. Expert Syst. Appl. 229(Part A): 120500 (2023) - [j17]Anders Parslov, Niklas Christoffer Petersen, Filipe Rodrigues:
Short-term bus travel time prediction for transfer synchronization with intelligent uncertainty handling. Expert Syst. Appl. 232: 120751 (2023) - 2022
- [j16]Daniele Gammelli, Kasper Pryds Rolsted, Dario Pacino, Filipe Rodrigues:
Generalized multi-output Gaussian process censored regression. Pattern Recognit. 129: 108751 (2022) - [j15]Daniele Gammelli, Filipe Rodrigues:
Recurrent flow networks: A recurrent latent variable model for density estimation of urban mobility. Pattern Recognit. 129: 108752 (2022) - [j14]Filipe Rodrigues, Nicola Ortelli, Michel Bierlaire, Francisco Câmara Pereira:
Bayesian Automatic Relevance Determination for Utility Function Specification in Discrete Choice Models. IEEE Trans. Intell. Transp. Syst. 23(4): 3126-3136 (2022) - [j13]Frederik Boe Hüttel, Inon Peled, Filipe Rodrigues, Francisco C. Pereira:
Modeling Censored Mobility Demand Through Censored Quantile Regression Neural Networks. IEEE Trans. Intell. Transp. Syst. 23(11): 21753-21765 (2022) - 2020
- [j12]Ioulia Markou, Filipe Rodrigues, Francisco C. Pereira:
Is Travel Demand Actually Deep? An Application in Event Areas Using Semantic Information. IEEE Trans. Intell. Transp. Syst. 21(2): 641-652 (2020) - [j11]Filipe Rodrigues, Francisco C. Pereira:
Beyond Expectation: Deep Joint Mean and Quantile Regression for Spatiotemporal Problems. IEEE Trans. Neural Networks Learn. Syst. 31(12): 5377-5389 (2020) - 2019
- [j10]Niklas Christoffer Petersen, Filipe Rodrigues, Francisco Câmara Pereira:
Multi-output bus travel time prediction with convolutional LSTM neural network. Expert Syst. Appl. 120: 426-435 (2019) - [j9]Filipe Rodrigues, Ioulia Markou, Francisco C. Pereira:
Combining time-series and textual data for taxi demand prediction in event areas: A deep learning approach. Inf. Fusion 49: 120-129 (2019) - [j8]Filipe Rodrigues, Kristian Henrickson, Francisco C. Pereira:
Multi-Output Gaussian Processes for Crowdsourced Traffic Data Imputation. IEEE Trans. Intell. Transp. Syst. 20(2): 594-603 (2019) - 2017
- [j7]Filipe Rodrigues, Stanislav Borysov, Bernardete Ribeiro, Francisco C. Pereira:
A Bayesian Additive Model for Understanding Public Transport Usage in Special Events. IEEE Trans. Pattern Anal. Mach. Intell. 39(11): 2113-2126 (2017) - [j6]Filipe Rodrigues, Mariana Lourenço, Bernardete Ribeiro, Francisco C. Pereira:
Learning Supervised Topic Models for Classification and Regression from Crowds. IEEE Trans. Pattern Anal. Mach. Intell. 39(12): 2409-2422 (2017) - 2015
- [j5]Francisco C. Pereira, Filipe Rodrigues, Moshe E. Ben-Akiva:
Using Data From the Web to Predict Public Transport Arrivals Under Special Events Scenarios. J. Intell. Transp. Syst. 19(3): 273-288 (2015) - [j4]Francisco C. Pereira, Filipe Rodrigues, Evgheni Polisciuc, Moshe E. Ben-Akiva:
Why so many people? Explaining Nonhabitual Transport Overcrowding With Internet Data. IEEE Trans. Intell. Transp. Syst. 16(3): 1370-1379 (2015) - [j3]Shan Jiang, Ana Alves, Filipe Rodrigues, Joseph Ferreira Jr., Francisco C. Pereira:
Mining point-of-interest data from social networks for urban land use classification and disaggregation. Comput. Environ. Urban Syst. 53: 36-46 (2015) - 2014
- [j2]Filipe Rodrigues, Francisco C. Pereira, Bernardete Ribeiro:
Sequence labeling with multiple annotators. Mach. Learn. 95(2): 165-181 (2014) - 2013
- [j1]Filipe Rodrigues, Francisco C. Pereira, Bernardete Ribeiro:
Learning from multiple annotators: Distinguishing good from random labelers. Pattern Recognit. Lett. 34(12): 1428-1436 (2013)
Conference and Workshop Papers
- 2023
- [c18]Alastair Ronald Main, Filipe Rodrigues, Dario Pacino:
The Dynamic RORO Stowage Planning Problem. ICCL 2023: 122-138 - [c17]Daniele Gammelli, James Harrison, Kaidi Yang, Marco Pavone, Filipe Rodrigues, Francisco C. Pereira:
Graph Reinforcement Learning for Network Control via Bi-Level Optimization. ICML 2023: 10587-10610 - [c16]Niklas Petersen, Filipe Rodrigues, Francisco C. Pereira:
Representation Learning of Rare Temporal Conditions for Travel Time Prediction. ITSC 2023: 4919-4926 - [c15]Filipe Rodrigues:
On the Importance of Stationarity, Strong Baselines and Benchmarks in Transport Prediction Problems. ITSC 2023: 4927-4932 - [c14]Mathias Niemann Tygesen, Mayank Sharan, Francisco C. Pereira, Filipe Rodrigues, Rose Yu:
Incident congestion propagation prediction using incident reports. SuMob@SIGSPATIAL 2023: 33-42 - 2022
- [c13]Daniele Gammelli, Kaidi Yang, James Harrison, Filipe Rodrigues, Francisco C. Pereira, Marco Pavone:
Graph Meta-Reinforcement Learning for Transferable Autonomous Mobility-on-Demand. KDD 2022: 2913-2923 - 2021
- [c12]Daniele Gammelli, Kaidi Yang, James Harrison, Filipe Rodrigues, Francisco C. Pereira, Marco Pavone:
Graph Neural Network Reinforcement Learning for Autonomous Mobility-on-Demand Systems. CDC 2021: 2996-3003 - 2019
- [c11]Filipe Rodrigues, Carlos Lima Azevedo:
Towards Robust Deep Reinforcement Learning for Traffic Signal Control: Demand Surges, Incidents and Sensor Failures. ITSC 2019: 3559-3566 - 2018
- [c10]Filipe Rodrigues, Francisco C. Pereira:
Deep Learning from Crowds. AAAI 2018: 1611-1618 - [c9]Ioulia Markou, Filipe Rodrigues, Francisco C. Pereira:
Real-Time Taxi Demand Prediction using data from the web. ITSC 2018: 1664-1671 - 2016
- [c8]Stanislav Borysov, Mariana Lourenço, Filipe Rodrigues, Alexander Balatsky, Francisco C. Pereira:
Using internet search queries to predict human mobility in social events. ITSC 2016: 1342-1347 - [c7]Adriana Ferrugento, Hugo Gonçalo Oliveira, Ana Alves, Filipe Rodrigues:
Can Topic Modelling benefit from Word Sense Information? LREC 2016 - 2015
- [c6]Adriana Ferrugento, Ana Alves, Hugo Gonçalo Oliveira, Filipe Rodrigues:
Towards the Improvement of a Topic Model with Semantic Knowledge. EPIA 2015: 759-770 - [c5]Filipe Rodrigues, Bernardete Ribeiro, Mariana Lourenço, Francisco C. Pereira:
Learning Supervised Topic Models from Crowds. HCOMP 2015: 160-168 - 2014
- [c4]Filipe Rodrigues, Francisco C. Pereira, Bernardete Ribeiro:
Gaussian Process Classification and Active Learning with Multiple Annotators. ICML 2014: 433-441 - [c3]Ana Alves, Adriana Ferrugento, Mariana Lourenço, Filipe Rodrigues:
ASAP: Automatic Semantic Alignment for Phrases. SemEval@COLING 2014: 104-108 - 2011
- [c2]Ana Oliveira Alves, Filipe Rodrigues, Francisco C. Pereira:
Tagging Space from Information Extraction and Popularity of Points of Interest. AmI 2011: 115-125 - 2010
- [c1]Ana Oliveira Alves, Francisco C. Pereira, Filipe Rodrigues, João Oliveirinha:
Place in Perspective: Extracting Online Information about Points of Interest. AmI 2010: 61-72
Informal and Other Publications
- 2024
- [i29]Carolin Schmidt, Mathias Niemann Tygesen, Filipe Rodrigues:
Arrival Time Prediction for Autonomous Shuttle Services in the Real World: Evidence from Five Cities. CoRR abs/2401.05322 (2024) - [i28]Frederik Boe Hüttel, Christoffer Riis, Filipe Rodrigues, Francisco Câmara Pereira:
Bayesian Active Learning for Censored Regression. CoRR abs/2402.11973 (2024) - 2023
- [i27]Frederik Boe Hüttel, Filipe Rodrigues, Francisco Câmara Pereira:
Mind the Gap - Modelling Difference Between Censored and Uncensored Electric Vehicle Charging Demand. CoRR abs/2301.06418 (2023) - [i26]Carolin Schmidt, Daniele Gammelli, Francisco Câmara Pereira, Filipe Rodrigues:
Learning to Control Autonomous Fleets from Observation via Offline Reinforcement Learning. CoRR abs/2302.14833 (2023) - [i25]Daniele Gammelli, James Harrison, Kaidi Yang, Marco Pavone, Filipe Rodrigues, Francisco C. Pereira:
Graph Reinforcement Learning for Network Control via Bi-Level Optimization. CoRR abs/2305.09129 (2023) - [i24]Frederik Boe Hüttel, Filipe Rodrigues, Francisco Câmara Pereira:
Deep Evidential Learning for Bayesian Quantile Regression. CoRR abs/2308.10650 (2023) - 2022
- [i23]Mathias Niemann Tygesen, Francisco C. Pereira, Filipe Rodrigues:
Unboxing the graph: Neural Relational Inference for Mobility Prediction. CoRR abs/2201.10307 (2022) - [i22]Daniele Gammelli, Kaidi Yang, James Harrison, Filipe Rodrigues, Francisco C. Pereira, Marco Pavone:
Graph Meta-Reinforcement Learning for Transferable Autonomous Mobility-on-Demand. CoRR abs/2202.07147 (2022) - 2021
- [i21]Georges Sfeir, Filipe Rodrigues, Maya Abou-Zeid:
Gaussian Process Latent Class Choice Models. CoRR abs/2101.12252 (2021) - [i20]Inon Peled, Filipe Rodrigues, Francisco C. Pereira:
Modeling Censored Mobility Demand through Quantile Regression Neural Networks. CoRR abs/2104.01214 (2021) - [i19]Niklas Christoffer Petersen, Anders Parslov, Filipe Rodrigues:
Short-term bus travel time prediction for transfer synchronization with intelligent uncertainty handling. CoRR abs/2104.06819 (2021) - [i18]Daniele Gammelli, Kaidi Yang, James Harrison, Filipe Rodrigues, Francisco C. Pereira, Marco Pavone:
Graph Neural Network Reinforcement Learning for Autonomous Mobility-on-Demand Systems. CoRR abs/2104.11434 (2021) - [i17]Frederik Boe Hüttel, Inon Peled, Filipe Rodrigues, Francisco C. Pereira:
Deep Spatio-Temporal Forecasting of Electrical Vehicle Charging Demand. CoRR abs/2106.10940 (2021) - [i16]Daniele Gammelli, Yihua Wang, Dennis Prak, Filipe Rodrigues, Stefan Minner, Francisco Câmara Pereira:
Predictive and Prescriptive Performance of Bike-Sharing Demand Forecasts for Inventory Management. CoRR abs/2108.00858 (2021) - 2020
- [i15]Daniele Gammelli, Inon Peled, Filipe Rodrigues, Dario Pacino, Haci A. Kurtaran, Francisco C. Pereira:
Estimating Latent Demand of Shared Mobility through Censored Gaussian Processes. CoRR abs/2001.07402 (2020) - [i14]Filipe Rodrigues:
Scaling Bayesian inference of mixed multinomial logit models to very large datasets. CoRR abs/2004.05426 (2020) - [i13]Daniele Gammelli, Filipe Rodrigues:
Recurrent Flow Networks: A Recurrent Latent Variable Model for Spatio-Temporal Density Modelling. CoRR abs/2006.05256 (2020) - [i12]Georges Sfeir, Maya Abou-Zeid, Filipe Rodrigues, Francisco Câmara Pereira, Isam Kaysi:
Semi-nonparametric Latent Class Choice Model with a Flexible Class Membership Component: A Mixture Model Approach. CoRR abs/2007.02739 (2020) - [i11]Daniele Gammelli, Kasper Pryds Rolsted, Dario Pacino, Filipe Rodrigues:
Generalized Multi-Output Gaussian Process Censored Regression. CoRR abs/2009.04822 (2020) - 2019
- [i10]Niklas Christoffer Petersen, Filipe Rodrigues, Francisco Câmara Pereira:
Multi-output Bus Travel Time Prediction with Convolutional LSTM Neural Network. CoRR abs/1903.02791 (2019) - [i9]Filipe Rodrigues, Carlos Lima Azevedo:
Towards Robust Deep Reinforcement Learning for Traffic Signal Control: Demand Surges, Incidents and Sensor Failures. CoRR abs/1904.08353 (2019) - [i8]Filipe Rodrigues, Nicola Ortelli, Michel Bierlaire, Francisco C. Pereira:
Bayesian Automatic Relevance Determination for Utility Function Specification in Discrete Choice Models. CoRR abs/1906.03855 (2019) - 2018
- [i7]Filipe Rodrigues, Ioulia Markou, Francisco C. Pereira:
Combining time-series and textual data for taxi demand prediction in event areas: a deep learning approach. CoRR abs/1808.05535 (2018) - [i6]Filipe Rodrigues, Mariana Lourenço, Bernardete Ribeiro, Francisco C. Pereira:
Learning Supervised Topic Models for Classification and Regression from Crowds. CoRR abs/1808.05902 (2018) - [i5]Filipe Rodrigues, Francisco C. Pereira:
Beyond expectation: Deep joint mean and quantile regression for spatio-temporal problems. CoRR abs/1808.08798 (2018) - [i4]Filipe Rodrigues, Francisco C. Pereira:
Heteroscedastic Gaussian processes for uncertainty modeling in large-scale crowdsourced traffic data. CoRR abs/1812.08733 (2018) - [i3]Filipe Rodrigues, Kristian Henrickson, Francisco C. Pereira:
Multi-Output Gaussian Processes for Crowdsourced Traffic Data Imputation. CoRR abs/1812.08739 (2018) - [i2]Filipe Rodrigues, Stanislav S. Borysov, Bernardete Ribeiro, Francisco C. Pereira:
A Bayesian Additive Model for Understanding Public Transport Usage in Special Events. CoRR abs/1812.08755 (2018) - 2017
- [i1]Filipe Rodrigues, Francisco C. Pereira:
Deep learning from crowds. CoRR abs/1709.01779 (2017)
Coauthor Index
aka: Francisco Câmara Pereira
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