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ORCIDRoss D. Shachter
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- affiliation: Stanford University
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2020 – today
- 2022
[p1]Ross D. Shachter, David Heckerman:
Why Did They Do That? Probabilistic and Causal Inference 2022: 805-812- 2021
- [c44]Samriddhi Singla, Ayan Mukhopadhyay, Michael Wilbur, Tina Diao, Vinayak Gajjewar, Ahmed Eldawy, Mykel J. Kochenderfer, Ross D. Shachter, Abhishek Dubey:
WildfireDB: An Open-Source Dataset Connecting Wildfire Occurrence with Relevant Determinants. NeurIPS Datasets and Benchmarks 2021 - 2020
- [c43]Tina Diao, Samriddhi Singla, Ayan Mukhopadhyay, Ahmed Eldawy, Ross D. Shachter, Mykel J. Kochenderfer:
Uncertainty Aware Wildfire Management. AI4SG@AAAI Fall Symposium 2020 - [i35]Tina Diao, Samriddhi Singla, Ayan Mukhopadhyay
, Ahmed Eldawy, Ross D. Shachter, Mykel J. Kochenderfer:
Uncertainty Aware Wildfire Management. CoRR abs/2010.07915 (2020)
2010 – 2019
- 2017
- [j16]Xi Chen, Ross D. Shachter, Allison W. Kurian, Daniel L. Rubin:
Dynamic strategy for personalized medicine: An application to metastatic breast cancer. J. Biomed. Informatics 68: 50-57 (2017) - 2016
- [c42]Ross D. Shachter:
Decisions and Dependence in Influence Diagrams. Probabilistic Graphical Models 2016: 462-473 - 2015
- [c41]Wenhao Liu, Ross D. Shachter:
Complexity of the Exact Solution to the Test Sequencing Problem. UAI 2015: 494-503 - 2013
- [c40]Charles Tripp, Ross D. Shachter:
Approximate Kalman Filter Q-Learning for Continuous State-Space MDPs. UAI 2013 - [i34]Ross D. Shachter:
Efficient Value of Information Computation. CoRR abs/1301.6739 (2013) - [i33]Mark Alan Peot, Ross D. Shachter:
Learning From What You Don't Observe. CoRR abs/1301.7407 (2013) - [i32]Ross D. Shachter:
Bayes-Ball: The Rational Pastime (for Determining Irrelevance and Requisite Information in Belief Networks and Influence Diagrams). CoRR abs/1301.7412 (2013) - [i31]Ross D. Shachter, Marvin Mandelbaum:
A Measure of Decision Flexibility. CoRR abs/1302.3603 (2013) - [i30]Tom Chávez, Ross D. Shachter:
Decision Flexibility. CoRR abs/1302.4937 (2013) - [i29]David Heckerman, Ross D. Shachter:
A Definition and Graphical Representation for Causality. CoRR abs/1302.4956 (2013) - [i28]Adriano Azevedo-Filho, Ross D. Shachter:
Laplace's Method Approximations for Probabilistic Inference in Belief Networks with Continuous Variables. CoRR abs/1302.6782 (2013) - [i27]David Heckerman, Ross D. Shachter:
A Decision-Based View of Causality. CoRR abs/1302.6816 (2013) - [i26]William B. Poland, Ross D. Shachter:
Three Approaches to Probability Model Selection. CoRR abs/1302.6838 (2013) - [i25]Ross D. Shachter, Stig K. Andersen, Peter Szolovits:
Global Conditioning for Probabilistic Inference in Belief Networks. CoRR abs/1302.6843 (2013) - [i24]Harold P. Lehmann, Ross D. Shachter:
End-User Construction of Influence Diagrams for Bayesian Statistics. CoRR abs/1303.1459 (2013) - [i23]William B. Poland, Ross D. Shachter:
Mixtures of Gaussians and Minimum Relative Entropy Techniques for Modeling Continuous Uncertainties. CoRR abs/1303.1476 (2013) - [i22]Ross D. Shachter, Pierre Ndilikilikesha:
Using Potential Influence Diagrams for Probabilistic Inference and Decision Making. CoRR abs/1303.1500 (2013) - [i21]Brian Y. Chan, Ross D. Shachter:
Structural Controllability and Observability in Influence Diagrams. CoRR abs/1303.5394 (2013) - [i20]Ross D. Shachter, Mark Alan Peot:
Decision Making Using Probabilistic Inference Methods. CoRR abs/1303.5428 (2013) - [i19]Ross D. Shachter:
A Graph-Based Inference Method for Conditional Independence. CoRR abs/1303.5749 (2013) - [i18]Ross D. Shachter, Stig K. Andersen, Kim-Leng Poh:
Directed Reduction Algorithms and Decomposable Graphs. CoRR abs/1304.1110 (2013) - [i17]Ross D. Shachter:
Evidence Absorption and Propagation through Evidence Reversals. CoRR abs/1304.1525 (2013) - [i16]Ross D. Shachter, Mark Alan Peot:
Simulation Approaches to General Probabilistic Inference on Belief Networks. CoRR abs/1304.1526 (2013) - [i15]Ross D. Shachter:
A Linear Approximation Method for Probabilistic Inference. CoRR abs/1304.2373 (2013) - [i14]Ross D. Shachter, David M. Eddy, Vic Hasselblad, Robert Wolpert:
A Heuristic Bayesian Approach to Knowledge Acquisition: Application to Analysis of Tissue-Type Plasminogen Activator. CoRR abs/1304.2737 (2013) - [i13]Ross D. Shachter, Leonard J. Bertrand:
Efficient Inference on Generalized Fault Diagrams. CoRR abs/1304.2758 (2013) - [i12]Ross D. Shachter, David Heckerman:
A Backwards View for Assessment. CoRR abs/1304.3107 (2013) - [i11]Ross D. Shachter:
DAVID: Influence Diagram Processing System for the Macintosh. CoRR abs/1304.3108 (2013) - [i10]Ross D. Shachter:
Intelligent Probabilistic Inference. CoRR abs/1304.3446 (2013) - [i9]Max Henrion, Laveen N. Kanal, John F. Lemmer, Ross D. Shachter:
Proceedings of the Fifth Conference on Uncertainty in Artificial Intelligence (1989). CoRR abs/1304.3855 (2013) - [i8]Laveen N. Kanal, John F. Lemmer, Tod S. Levitt, Ross D. Shachter:
Proceedings of the Fourth Conference on Uncertainty in Artificial Intelligence (1988). CoRR abs/1304.3856 (2013) - [i7]Charles Tripp, Ross D. Shachter:
Approximate Kalman Filter Q-Learning for Continuous State-Space MDPs. CoRR abs/1309.6868 (2013) - 2012
- [j15]Debarun Bhattacharjya, Ross D. Shachter:
Formulating Asymmetric Decision Problems as Decision Circuits. Decis. Anal. 9(2): 138-145 (2012) - [c39]Charles Tripp, Ross D. Shachter:
Backtracking for More Efficient Large Scale Dynamic Programming. ICMLA (1) 2012: 338-343 - [i6]SangIn Chun, Ross D. Shachter:
Strictly Proper Mechanisms with Cooperating Players. CoRR abs/1202.3710 (2012) - [i5]Debarun Bhattacharjya, Ross D. Shachter:
Three new sensitivity analysis methods for influence diagrams. CoRR abs/1203.3467 (2012) - [i4]Ross D. Shachter, Debarun Bhattacharjya:
Dynamic programming in in uence diagrams with decision circuits. CoRR abs/1203.3513 (2012) - [i3]Debarun Bhattacharjya, Ross D. Shachter:
Sensitivity analysis in decision circuits. CoRR abs/1206.3551 (2012) - [i2]Debarun Bhattacharjya, Ross D. Shachter:
Evaluating influence diagrams with decision circuits. CoRR abs/1206.5257 (2012) - 2011
- [c38]SangIn Chun, Ross D. Shachter:
Strictly Proper Mechanisms with Cooperating Players. UAI 2011: 125-134 - 2010
- [c37]Debarun Bhattacharjya, Ross D. Shachter:
Three new sensitivity analysis methods for influence diagrams. UAI 2010: 56-64 - [c36]Ross D. Shachter, Debarun Bhattacharjya:
Dynamic programming in in uence diagrams with decision circuits. UAI 2010: 509-516
2000 – 2009
- 2008
- [c35]Debarun Bhattacharjya, Ross D. Shachter:
Sensitivity analysis in decision circuits. UAI 2008: 34-42 - 2007
- [c34]Debarun Bhattacharjya, Ross D. Shachter:
Evaluating influence diagrams with decision circuits. UAI 2007: 9-16 - 2005
- [j14]Apiruk Detwarasiti, Ross D. Shachter:
Influence Diagrams for Team Decision Analysis. Decis. Anal. 2(4): 207-228 (2005) - [j13]George C. Scott, Ross D. Shachter:
Individualizing generic decision models using assessments as evidence. J. Biomed. Informatics 38(4): 281-297 (2005) - 2004
- [c33]Elizabeth S. Burnside, Daniel L. Rubin, Ross D. Shachter:
Improving a Bayesian network's ability to predict the probability of malignancy of microcalcifications on mammography. CARS 2004: 1021-1026 - [c32]Elizabeth S. Burnside, Daniel L. Rubin, Ross D. Shachter:
Using a Bayesian Network to Predict the Probability and Type of Breast Cancer Represented by Microcalcifications on Mammography. MedInfo 2004: 13-17 - 2002
- [c31]George C. Scott, Ross D. Shachter, Leslie A. Lenert:
An Approach to Automate and Individualize Interactive Decision Support for Patients. AMIA 2002 - 2001
- [c30]Daniel G. Shapiro, Pat Langley, Ross D. Shachter:
Using background knowledge to speed reinforcement learning in physical agents. Agents 2001: 254-261 - [c29]George C. Scott, Ross D. Shachter, Leslie A. Lenert:
SecondOpinion: A Framework for Using Decision Models to Automate and Individualize Interactive Patient-oriented Decision Support Aids. AMIA 2001 - [c28]George C. Scott, Ross D. Shachter, Leslie A. Lenert:
Using Decision Models To Automate and Individualize Interactive Patient-oriented Decision Support Aids. AMIA 2001 - 2000
- [c27]Elizabeth S. Burnside, Daniel L. Rubin, Ross D. Shachter:
A Bayesian network for mammography. AMIA 2000
1990 – 1999
- 1999
- [c26]Ross D. Shachter:
Efficient Value of Information Computation. UAI 1999: 594-601 - 1998
- [j12]Donna M. Edwards, Ross D. Shachter, Douglas K. Owens:
A Dynamic HIV-Transmission Model for Evaluating the Costs and Benefits of Vaccine Programs. Interfaces 28(3): 144-166 (1998) - [c25]Mark A. Peot, Ross D. Shachter:
Learning From What You Don't Observe. UAI 1998: 439-446 - [c24]Ross D. Shachter:
Bayes-Ball: The Rational Pastime (for Determining Irrelevance and Requisite Information in Belief Networks and Influence Diagrams). UAI 1998: 480-487 - 1996
- [c23]Ross D. Shachter, Marvin Mandelbaum:
A Measure of Decision Flexibility. UAI 1996: 485-491 - 1995
- [j11]David Heckerman, Ross D. Shachter:
Decision-Theoretic Foundations for Causal Reasoning. J. Artif. Intell. Res. 3: 405-430 (1995) - [c22]Tom Chávez, Ross D. Shachter:
Decision Flexibility. UAI 1995: 77-86 - [c21]David Heckerman, Ross D. Shachter:
A Definition and Graphical Representation for Causality. UAI 1995: 262-273 - [i1]David Heckerman, Ross D. Shachter:
Decision-Theoretic Foundations for Causal Reasoning. CoRR abs/cs/9512104 (1995) - 1994
- [c20]Adriano Azevedo-Filho, Ross D. Shachter:
Laplace's Method Approximations for Probabilistic Inference in Belief Networks with Continuous Variables. UAI 1994: 28-36 - [c19]David Heckerman, Ross D. Shachter:
A Decision-based View of Causality. UAI 1994: 302-310 - [c18]William B. Poland, Ross D. Shachter:
Three Approaches to Probability Model Selection. UAI 1994: 478-483 - [c17]Ross D. Shachter, Stig K. Andersen, Peter Szolovits:
Global Conditioning for Probabilistic Inference in Belief Networks. UAI 1994: 514-522 - 1993
- [c16]Harold P. Lehmann, Ross D. Shachter:
End-User Construction of Influence Diagrams for Bayesian Statistics. UAI 1993: 48-54 - [c15]William B. Poland, Ross D. Shachter:
Mixtures of Gaussians and Minimum Relative Entropy Techniques for Modeling Continuous Uncertainties. UAI 1993: 183-190 - [c14]Ross D. Shachter, Pierre Ndilikilikesha:
Using Potential Influence Diagrams for Probabilistic Inference and Decision Making. UAI 1993: 383-390 - 1992
- [j10]Holly B. Jimison, Lawrence M. Fagan, Ross D. Shachter, Edward H. Shortliffe:
Patient-specific explanation in models of chronic disease. Artif. Intell. Medicine 4(3): 191-205 (1992) - [c13]Brian Y. Chan, Ross D. Shachter:
Structural Controllability and Observability in Influence Diagrams. UAI 1992: 25-32 - [c12]Ross D. Shachter, Mark A. Peot:
Decision Making Using Probabilistic Inference Methods. UAI 1992: 276-283 - 1991
- [j9]Mark A. Peot, Ross D. Shachter:
Fusion and Propagation with Multiple Observations in Belief Networks. Artif. Intell. 48(3): 299-318 (1991) - [c11]Ross D. Shachter:
A Graph-Based Inference Method for Conditional Independence. UAI 1991: 353-360 - 1990
- [j8]Ross D. Shachter:
Introduction. Networks 20(5): 487-489 (1990) - [j7]Ross D. Shachter:
An ordered examination of influence diagrams. Networks 20(5): 535-563 (1990) - [j6]Joseph A. Tatman, Ross D. Shachter:
Dynamic programming and influence diagrams. IEEE Trans. Syst. Man Cybern. 20(2): 365-379 (1990) - [c10]Ross D. Shachter, Bruce D'Ambrosio, Brendan Del Favero:
Symbolic Probabilistic Inference in Belief Networks. AAAI 1990: 126-131 - [c9]Ross D. Shachter, Stig K. Andersen, Kim-Leng Poh:
Directed reduction algorithms and decomposable graphs. UAI 1990: 197-208 - [e2]Ross D. Shachter, Tod S. Levitt, Laveen N. Kanal, John F. Lemmer:
UAI '88: Proceedings of the Fourth Annual Conference on Uncertainty in Artificial Intelligence, Minneapolis, MN, USA, July 10-12, 1988. North-Holland 1990, ISBN 0-444-88650-8 [contents] - [e1]Max Henrion, Ross D. Shachter, Laveen N. Kanal, John F. Lemmer:
UAI '89: Proceedings of the Fifth Annual Conference on Uncertainty in Artificial Intelligence, Windsor, Ontario, Canada, August 18-20, 1989. North-Holland 1990, ISBN 0-444-88738-5 [contents]
1980 – 1989
- 1989
- [c8]Ross D. Shachter:
Evidence Absorption and Propagation through Evidence Reversals. UAI 1989: 173-190 - [c7]Ross D. Shachter, Mark A. Peot:
Simulation Approaches to General Probabilistic Inference on Belief Networks. UAI 1989: 221-234 - 1988
- [j5]Ross D. Shachter:
Efficient inference on generalized fault diagrams. Int. J. Approx. Reason. 2(3): 342 (1988) - [j4]Ross D. Shachter, David M. Eddy, Vic Hasselblad, Robert Wolpert:
A heuristic Bayesian approach to knowledge acquisition: Application to analysis of tissue-type plasminogen activator. Int. J. Approx. Reason. 2(3): 342 (1988) - [j3]Ross D. Shachter:
Probabilistic Inference and Influence Diagrams. Oper. Res. 36(4): 589-604 (1988) - [c6]Ross D. Shachter:
A linear approximation method for probabilistic inference. UAI 1988: 93-104 - 1987
- [j2]Ross D. Shachter, David Heckerman:
Thinking Backward for Knowledge Acquisition. AI Mag. 8(3): 55-61 (1987) - [c5]Ross D. Shachter, David M. Eddy, Vic Hasselblad, Robert Wolpert:
A Heuristic Bayesian Approach to Knowledge Acquisition: Application to the Analysis of Tissue-Type Plasminogen Activator. UAI 1987: 183-190 - [c4]Ross D. Shachter, Leonard J. Bertrand:
Efficient Inference on Generalized Fault Diagrams. UAI 1987: 325-332 - 1986
- [j1]Ross D. Shachter:
Evaluating Influence Diagrams. Oper. Res. 34(6): 871-882 (1986) - [c3]Ross D. Shachter:
DAVID: influence diagram processing system for the macintosh. UAI 1986: 191-196 - [c2]Ross D. Shachter, David Heckerman:
A backwards view for assessment. UAI 1986: 317-324 - 1985
- [c1]Ross D. Shachter:
Intelligent Probabilistic Inference. UAI 1985: 371-382
Coauthor Index
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