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ORCIDJoachim Giesen
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- affiliation: University of Jena, Germany
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2020 – today
- 2024
[j34]Joachim Giesen, Philipp Lucas, Linda Pfeiffer, Laines Schmalwasser, Kai Lawonn:
The whole and its parts: Visualizing Gaussian mixture models. Vis. Informatics 8(1): 67-79 (2024)- [c83]Andreas Goral, Joachim Giesen, Mark Blacher
, Christoph Staudt, Julien Klaus:
Model Counting and Sampling via Semiring Extensions. AAAI 2024: 20395-20403 - [c82]Paul Gerhardt Rump, Niklas Merk, Julien Klaus, Maurice Wenig, Joachim Giesen:
Convexity Certificates for Symbolic Tensor Expressions. IJCAI 2024: 1953-1960 - [c81]Paul Kahlmeyer, Joachim Giesen, Michael Habeck, Henrik Voigt:
Scaling Up Unbiased Search-based Symbolic Regression. IJCAI 2024: 4264-4272 - [c80]Christoph Staudt, Mark Blacher, Julien Klaus, Farin Lippmann, Joachim Giesen:
Improved Cut Strategy for Tensor Network Contraction Orders. SEA 2024: 27:1-27:19 - 2023
- [j33]Joachim Giesen, Paul Kahlmeyer, Sören Laue, Matthias Mitterreiter, Frank Nussbaum, Christoph Staudt:
Mixed membership Gaussians. J. Multivar. Anal. 195: 105141 (2023) - [j32]Mark Blacher, Julien Klaus, Christoph Staudt, Sören Laue, Viktor Leis, Joachim Giesen:
Efficient and Portable Einstein Summation in SQL. Proc. ACM Manag. Data 1(2): 121:1-121:19 (2023) - [j31]Kai Lawonn, Monique Meuschke, Pepe Eulzer, Matthias Mitterreiter, Joachim Giesen, Tobias Günther:
GRay: Ray Casting for Visualization and Interactive Data Exploration of Gaussian Mixture Models. IEEE Trans. Vis. Comput. Graph. 29(1): 526-536 (2023) - [j30]Julien Klaus, Mark Blacher, Andreas Goral, Philipp Lucas, Joachim Giesen:
A visual analytics workflow for probabilistic modeling. Vis. Informatics 7(2): 72-84 (2023) - [c79]Matthias Mitterreiter, Marcel Koch, Joachim Giesen, Sören Laue:
Why Capsule Neural Networks Do Not Scale: Challenging the Dynamic Parse-Tree Assumption. AAAI 2023: 9209-9216 - [c78]Julien Klaus, Mark Blacher, Joachim Giesen:
Compiling Tensor Expressions into Einsum. ICCS (2) 2023: 129-136 - [i13]Matthias Mitterreiter, Marcel Koch, Joachim Giesen, Sören Laue:
Why Capsule Neural Networks Do Not Scale: Challenging the Dynamic Parse-Tree Assumption. CoRR abs/2301.01583 (2023) - 2022
- [j29]Jan Wassenberg, Mark Blacher, Joachim Giesen, Peter Sanders:
Vectorized and performance-portable quicksort. Softw. Pract. Exp. 52(12): 2684-2699 (2022) - [j28]Shenghui Cheng, Joachim Giesen, Tianyi Huang, Philipp Lucas, Klaus Mueller:
Identifying the skeptics and the undecided through visual cluster analysis of local network geometry. Vis. Informatics 6(3): 11-22 (2022) - [c77]Sören Laue, Mark Blacher, Joachim Giesen:
Optimization for Classical Machine Learning Problems on the GPU. AAAI 2022: 7300-7308 - [c76]Mark Blacher, Joachim Giesen, Sören Laue, Julien Klaus, Viktor Leis:
Machine Learning, Linear Algebra, and More: Is SQL All You Need? CIDR 2022 - [c75]Julien Klaus, Mark Blacher, Joachim Giesen, Paul Gerhardt Rump, Konstantin Wiedom:
Compiling Linear Algebra Expressions into Efficient Code. ICCS (1) 2022: 11-17 - [c74]Joachim Giesen, Paul Kahlmeyer, Frank Nussbaum, Sina Zarrieß:
Leveraging the Wikipedia Graph for Evaluating Word Embeddings. IJCAI 2022: 4136-4142 - [c73]Julien Klaus, Niklas Merk, Konstantin Wiedom, Sören Laue, Joachim Giesen:
Convexity Certificates from Hessians. NeurIPS 2022 - [p2]Joachim Giesen, Lars Kuehne, Sören Laue:
The GENO Software Stack. Algorithms for Big Data 2022: 213-228 - [i12]Sören Laue, Mark Blacher, Joachim Giesen:
Optimization for Classical Machine Learning Problems on the GPU. CoRR abs/2203.16340 (2022) - [i11]Mark Blacher, Joachim Giesen, Peter Sanders, Jan Wassenberg:
Vectorized and performance-portable Quicksort. CoRR abs/2205.05982 (2022) - [i10]Julien Klaus, Niklas Merk, Konstantin Wiedom, Sören Laue, Joachim Giesen:
Convexity Certificates from Hessians. CoRR abs/2210.10430 (2022) - 2021
- [j27]Philipp Lucas, Joachim Giesen:
Lumen: A software for the interactive visualization of probabilistic models together with data. J. Open Source Softw. 6(63): 3395 (2021) - [c72]Joachim Giesen, Paul Kahlmeyer, Sören Laue, Matthias Mitterreiter, Frank Nussbaum, Christoph Staudt, Sina Zarrieß:
Method of Moments for Topic Models with Mixed Discrete and Continuous Features. IJCAI 2021: 2418-2424 - [c71]Frank Nussbaum, Joachim Giesen:
Robust principal component analysis for generalized multi-view models. UAI 2021: 686-695 - [c70]Mark Blacher, Joachim Giesen, Lars Kuehne:
Fast and Robust Vectorized In-Place Sorting of Primitive Types. SEA 2021: 3:1-3:16 - 2020
- [j26]Sören Laue, Matthias Mitterreiter, Joachim Giesen:
A Simple and Efficient Tensor Calculus for Machine Learning. Fundam. Informaticae 177(2): 157-179 (2020) - [j25]Joachim Giesen, Sören Laue, Matthias Mitterreiter:
Optimization frameworks for machine learning: Examples and case study. it Inf. Technol. 62(3-4): 169-180 (2020) - [j24]Frank Nussbaum, Joachim Giesen:
Pairwise sparse + low-rank models for variables of mixed type. J. Multivar. Anal. 178: 104601 (2020) - [c69]Sören Laue, Matthias Mitterreiter, Joachim Giesen:
A Simple and Efficient Tensor Calculus. AAAI 2020: 4527-4534 - [c68]Sören Laue, Matthias Mitterreiter, Joachim Giesen:
GENO - Optimization for Classical Machine Learning Made Fast and Easy. AAAI 2020: 13620-13621 - [c67]Frank Nussbaum, Joachim Giesen:
Disentangling Direct and Indirect Interactions in Polytomous Item Response Theory Models. IJCAI 2020: 2241-2247 - [c66]Mark Blacher, Joachim Giesen, Sören Laue, Julien Klaus, Matthias Mitterreiter:
Fast Entity Resolution With Mock Labels and Sorted Integer Sets. DI2KG@VLDB 2020 - [i9]Sören Laue, Matthias Mitterreiter, Joachim Giesen:
A Simple and Efficient Tensor Calculus for Machine Learning. CoRR abs/2010.03313 (2020)
2010 – 2019
- 2019
- [j23]Joachim Giesen, Julien Klaus, Sören Laue, Ferdinand Schreck:
Visualization Support for Developing a Matrix Calculus Algorithm: A Case Study. Comput. Graph. Forum 38(3): 351-361 (2019) - [c65]Joachim Giesen, Sören Laue, Andreas Löhne, Christopher Schneider:
Using Benson's Algorithm for Regularization Parameter Tracking. AAAI 2019: 3689-3696 - [c64]Frank Nussbaum, Joachim Giesen:
Ising Models with Latent Conditional Gaussian Variables. ALT 2019: 669-681 - [c63]Joachim Giesen, Frank Nussbaum, Christopher Schneider:
Efficient Regularization Parameter Selection for Latent Variable Graphical Models via Bi-Level Optimization. IJCAI 2019: 2378-2384 - [c62]Joachim Giesen, Sören Laue:
Combining ADMM and the Augmented Lagrangian Method for Efficiently Handling Many Constraints. IJCAI 2019: 4525-4531 - [c61]Sören Laue, Matthias Mitterreiter, Joachim Giesen:
GENO - GENeric Optimization for Classical Machine Learning. NeurIPS 2019: 2187-2198 - [c60]Sören Laue, Matthias Mitterreiter, Joachim Giesen:
MatrixCalculus.org - Computing Derivatives of Matrix and Tensor Expressions. ECML/PKDD (3) 2019: 769-772 - [i8]Frank Nussbaum, Joachim Giesen:
Ising Models with Latent Conditional Gaussian Variables. CoRR abs/1901.09712 (2019) - [i7]Sören Laue, Matthias Mitterreiter, Joachim Giesen:
GENO - GENeric Optimization for Classical Machine Learning. CoRR abs/1905.13587 (2019) - 2018
- [c59]Sören Laue, Matthias Mitterreiter, Joachim Giesen:
Computing Higher Order Derivatives of Matrix and Tensor Expressions. NeurIPS 2018: 2755-2764 - 2017
- [j22]Joachim Giesen, Lars Kuehne, P. Lucas:
Sclow Plots: Visualizing Empty Space. Comput. Graph. Forum 36(3): 145-155 (2017) - 2016
- [i6]Joachim Giesen, Sören Laue:
Distributed Convex Optimization with Many Convex Constraints. CoRR abs/1610.02967 (2016) - 2015
- [c58]Katharina Blechschmidt, Joachim Giesen, Sören Laue:
Tracking Approximate Solutions of Parameterized Optimization Problems over Multi-Dimensional (Hyper-)Parameter Domains. ICML 2015: 438-447 - [c57]Joachim Giesen, Sören Laue, Jens K. Müller:
Reconstructing a Sparse Solution from a Compressed Support Vector Machine. MACIS 2015: 305-319 - 2014
- [c56]Joachim Giesen, Sören Laue, Lars Kuehne:
Sketching the Support of a Probability Measure. AISTATS 2014: 257-265 - [c55]Joachim Giesen, Sören Laue, Patrick Wieschollek:
Robust and Efficient Kernel Hyperparameter Paths with Guarantees. ICML 2014: 1296-1304 - 2013
- [c54]Joachim Giesen, Lars Kuehne:
A parallel algorithm for computing the flow complex. SoCG 2013: 57-66 - [i5]Artur Andrzejak, Joachim Giesen, Raghu Ramakrishnan, Ion Stoica:
Parallel Data Analysis (Dagstuhl Seminar 13251). Dagstuhl Reports 3(6): 67-82 (2013) - 2012
- [j21]Joachim Giesen, Balint Miklos, Mark Pauly:
The medial axis of the union of inner Voronoi balls in the plane. Comput. Geom. 45(9): 515-523 (2012) - [j20]Joachim Giesen, Martin Jaggi, Sören Laue:
Approximating parameterized convex optimization problems. ACM Trans. Algorithms 9(1): 10:1-10:17 (2012) - [j19]Lars Kuehne, Joachim Giesen, Zhiyuan Zhang, Sungsoo Ha, Klaus Mueller:
A Data-Driven Approach to Hue-Preserving Color-Blending. IEEE Trans. Vis. Comput. Graph. 18(12): 2122-2129 (2012) - [c53]Joachim Giesen, Martin Jaggi, Sören Laue:
Optimizing over the Growing Spectrahedron. ESA 2012: 503-514 - [c52]Joachim Giesen, Jens K. Müller, Sören Laue, Sascha Swiercy:
Approximating Concavely Parameterized Optimization Problems. NIPS 2012: 2114-2122 - [c51]Joachim Giesen, Martin Jaggi, Sören Laue:
Regularization Paths with Guarantees for Convex Semidefinite Optimization. AISTATS 2012: 432-439 - 2011
- [c50]Peter Zolliker, Zofia Baranczuk, Joachim Giesen:
Image Fusion for optimizing Gamut Mapping. CIC 2011: 109-114 - 2010
- [j18]Peter Zolliker, Zofia Baranczuk, Iris Sprow, Joachim Giesen:
Conjoint Analysis for Evaluating Parameterized Gamut Mapping Algorithms. IEEE Trans. Image Process. 19(3): 758-769 (2010) - [j17]Balint Miklos, Joachim Giesen, Mark Pauly:
Discrete scale axis representations for 3D geometry. ACM Trans. Graph. 29(4): 101:1-101:10 (2010) - [c49]Remco C. Veltkamp, Geert-Jan Giezeman, Hannah Bast, Thomas Baumbach, Takahiko Furuya, Joachim Giesen, Afzal Godil, Zhouhui Lian, Ryutarou Ohbuchi, Waqar Saleem:
SHREC'10 Track: Large Scale Retrieval. 3DOR@Eurographics 2010: 63-69 - [c48]Joachim Giesen, Martin Jaggi, Sören Laue:
Approximating Parameterized Convex Optimization Problems. ESA (1) 2010: 524-535 - [p1]Joachim Giesen, Klaus Mueller, Bilyana Taneva, Peter Zolliker:
Choice-Based Conjoint Analysis: Classification vs. Discrete Choice Models. Preference Learning 2010: 297-315
2000 – 2009
- 2009
- [j16]Joachim Giesen, Eva Schuberth, Milos Stojakovic:
Approximate Sorting. Fundam. Informaticae 90(1-2): 67-72 (2009) - [c47]Joachim Giesen, Balint Miklos, Mark Pauly, Camille Wormser:
The scale axis picture show. SCG 2009: 94-95 - [c46]Joachim Giesen, Balint Miklos, Mark Pauly, Camille Wormser:
The scale axis transform. SCG 2009: 106-115 - [c45]Zofia Baranczuk, Peter Zolliker, Joachim Giesen:
Image Quality Measures for Evaluating Gamut Mapping. CIC 2009: 21-26 - [i4]Joachim Giesen, Madhusudan Manjunath:
Minimizing Absolute Gaussian Curvature Locally. Computational Geometry 2009 - [i3]Bernd Gärtner, Joachim Giesen, Martin Jaggi:
An Exponential Lower Bound on the Complexity of Regularization Paths. CoRR abs/0903.4817 (2009) - [i2]Bernd Gärtner, Joachim Giesen, Martin Jaggi, Torsten Welsch:
A Combinatorial Algorithm to Compute Regularization Paths. CoRR abs/0903.4856 (2009) - 2008
- [j15]Joachim Giesen, Matthias John:
The flow complex: A data structure for geometric modeling. Comput. Geom. 39(3): 178-190 (2008) - [j14]Kevin Buchin, Tamal K. Dey, Joachim Giesen, Matthias John:
Recursive geometry of the flow complex and topology of the flow complex filtration. Comput. Geom. 40(2): 115-137 (2008) - [j13]Tamal K. Dey, Joachim Giesen, Edgar A. Ramos, Bardia Sadri:
Critical Points of Distance to an epsilon-Sampling of a Surface and Flow-Complex-Based Surface Reconstruction. Int. J. Comput. Geom. Appl. 18(1/2): 29-61 (2008) - [j12]Joachim Giesen, Edgar A. Ramos, Bardia Sadri:
Medial Axis Approximation and Unstable Flow Complex. Int. J. Comput. Geom. Appl. 18(6): 533-565 (2008) - [j11]Lujin Wang, Joachim Giesen, Kevin T. McDonnell, Peter Zolliker, Klaus Mueller:
Color Design for Illustrative Visualization. IEEE Trans. Vis. Comput. Graph. 14(6): 1739-1754 (2008) - [c44]Joachim Giesen, Madhusudan Manjunath, Michael Eigensatz:
The Solution Path of the Slab Support Vector Machine. CCCG 2008 - [c43]Zofia Baranczuk, Iris Sprow, Peter Zolliker, Joachim Giesen:
Conjoint Analysis of Parametrized Gamut Mapping Algorithms. CIC 2008: 38-43 - 2007
- [j10]Tamal K. Dey, Joachim Giesen, Samrat Goswami:
Delaunay triangulations approximate anchor hulls. Comput. Geom. 36(2): 131-143 (2007) - [j9]Joachim Giesen, Eva Schuberth, Klaus Simon, Peter Zolliker, Oliver Zweifel:
Image-Dependent Gamut Mapping as Optimization Problem. IEEE Trans. Image Process. 16(10): 2401-2410 (2007) - [j8]Joachim Giesen, Klaus Mueller, Eva Schuberth, Lujin Wang, Peter Zolliker:
Conjoint Analysis to Measure the Perceived Quality in Volume Rendering. IEEE Trans. Vis. Comput. Graph. 13(6): 1664-1671 (2007) - [c42]Joachim Giesen, Dieter Mitsche, Eva Schuberth:
Collaborative Ranking: An Aggregation Algorithm for Individuals' Preference Estimation. AAIM 2007: 58-67 - [c41]Joachim Giesen, Balint Miklos, Mark Pauly:
Medial Axis Approximation of Planar Shapes from Union of Balls: A Simpler and more Robust Algorithm. CCCG 2007: 105-108 - [c40]Balint Miklos, Joachim Giesen, Mark Pauly:
Medial axis approximation from inner Voronoi balls: a demo of the Mesecina tool. SCG 2007: 123-124 - 2006
- [j7]Joachim Giesen, Frédéric Cazals, Mark Pauly, Afra Zomorodian:
The conformal alpha shape filtration. Vis. Comput. 22(8): 531-540 (2006) - [c39]Joachim Giesen, Eva Schuberth, Klaus Simon, Daniel Zeiter, Peter Zolliker:
A framework for image-dependent gamut mapping. Color Imaging: Processing, Hardcopy, and Applications 2006: 605805 - [c38]Joachim Giesen, Edgar A. Ramos, Bardia Sadri:
Medial axis approximation and unstable flow complex. SCG 2006: 327-336 - [c37]Joachim Giesen, Eva Schuberth, Klaus Simon, Peter Zolliker:
A kernel approach to gamut boundary computation. EUSIPCO 2006: 1-4 - [c36]Joachim Giesen, Eva Schuberth, Milos Stojakovic:
Approximate Sorting. LATIN 2006: 524-531 - [c35]Niloy J. Mitra, Leonidas J. Guibas, Joachim Giesen, Mark Pauly:
Probabilistic fingerprints for shapes. Symposium on Geometry Processing 2006: 121-130 - 2005
- [c34]Maike Buchin, Joachim Giesen:
Minimizing the Total Absolute Gaussian Curvature in a Terrain is Hard. CCCG 2005: 195-198 - [c33]Kevin Buchin, Joachim Giesen:
Flow Complex: General Structure and Algorithm. CCCG 2005: 270-273 - [c32]Joachim Giesen, Eva Schuberth, Klaus Simon, Peter Zolliker:
Toward image-dependent gamut mapping: fast and accurate gamut boundary determination. Color Imaging: Processing, Hardcopy, and Applications 2005: 201-210 - [c31]Tamal K. Dey, Joachim Giesen, Edgar A. Ramos, Bardia Sadri:
Critical points of the distance to an epsilon-sampling of a surface and flow-complex-based surface reconstruction. SCG 2005: 218-227 - [c30]Joachim Giesen, Dieter Mitsche:
Reconstructing Many Partitions Using Spectral Techniques. FCT 2005: 433-444 - [c29]Joachim Giesen, Dieter Mitsche:
Boosting Spectral Partitioning by Sampling and Iteration. ISAAC 2005: 473-482 - [c28]Mark Pauly, Niloy J. Mitra, Joachim Giesen, Markus H. Gross, Leonidas J. Guibas:
Example-Based 3D Scan Completion. Symposium on Geometry Processing 2005: 23-32 - [c27]Tamal K. Dey, Joachim Giesen, Samrat Goswami:
Delaunay triangulations approximate anchor hulls. SODA 2005: 1028-1037 - [c26]Frédéric Cazals, Joachim Giesen, Mark Pauly, Afra Zomorodian:
Conformal Alpha Shapes. PBG 2005: 55-61 - [c25]Joachim Giesen, Dieter Mitsche:
Bounding the Misclassification Error in Spectral Partitioning in the Planted Partition Model. WG 2005: 409-420 - 2004
- [j6]Joachim Giesen, Uli Wagner:
Shape Dimension and Intrinsic Metric from Samples of Manifolds. Discret. Comput. Geom. 32(2): 245-267 (2004) - [c24]Joachim Giesen, Simon Spalinger:
Meshless surface reconstruction by kernel clustering. CCCG 2004: 11-14 - [c23]Bernhard Schölkopf, Joachim Giesen, Simon Spalinger:
Kernel Methods for Implicit Surface Modeling. NIPS 2004: 1193-1200 - [c22]Mattias Andersson, Joachim Giesen, Mark Pauly, Bettina Speckmann:
Bounds on the k-Neighborhood for Locally Uniformly Sampled Surfaces. PBG 2004: 167-171 - [c21]Tamal K. Dey, Joachim Giesen, Samrat Goswami:
Shape Segmentation and Matching from Noisy Point Clouds. PBG 2004: 193-199 - 2003
- [j5]Tamal K. Dey, Joachim Giesen, Samrat Goswami, Wulue Zhao:
Shape Dimension and Approximation from Samples. Discret. Comput. Geom. 29(3): 419-434 (2003) - [j4]Joachim Giesen, Matthias John, Michel Stöcklin:
Symmetry of Flow Diagrams Derived from Weighted Points in the Plane. Int. J. Comput. Geom. Appl. 13(4): 327-337 (2003) - [c20]Joachim Giesen, Uli Wagner:
Shape dimension and intrinsic metric from samples of manifolds with high co-dimension. SCG 2003: 329-337 - [c19]Joachim Giesen, Matthias John:
The flow complex: a data structure for geometric modeling. SODA 2003: 285-294 - [c18]Tamal K. Dey, Joachim Giesen, Matthias John:
Alpha-shapes and flow shapes are homotopy equivalent. STOC 2003: 493-502 - [c17]Joachim Giesen, Matthias John:
Computing the Weighted Flow Complex. VMV 2003: 235-243 - [c16]Tamal K. Dey, Joachim Giesen, Samrat Goswami:
Shape Segmentation and Matching with Flow Discretization. WADS 2003: 25-36 - 2002
- [j3]Joachim Giesen, Matthias John:
Surface reconstruction based on a dynamical system. Comput. Graph. Forum 21(3): 363-371 (2002) - [j2]Udo Adamy, Joachim Giesen, Matthias John:
Surface reconstruction using umbrella filters. Comput. Geom. 21(1-2): 63-86 (2002) - [c15]Joachim Giesen, Matthias John:
The complexity of flow diagrams in the plane. CCCG 2002: 45-48 - [c14]Joachim Giesen, Matthias John:
Duality in Disk Induced Flows. International Conference on Computational Science (3) 2002: 154-163 - [c13]Joachim Giesen, Axel Völker:
Requirements Interdependencies and Stakeholders Preferences. RE 2002: 206-212 - [c12]Joachim Giesen, Roger Wattenhofer, Aaron Zollinger:
Towards a Theory of Peer-to-Peer Computability. SIROCCO 2002: 115-132 - [c11]Tamal K. Dey, Joachim Giesen, Samrat Goswami, Wulue Zhao:
Shape dimension and approximation from samples. SODA 2002: 772-780 - [c10]Joachim Giesen, Matthias John:
A New Diagram from Disks in the Plane. STACS 2002: 238-249 - 2001
- [c9]Tamal K. Dey, Joachim Giesen, James Hudson:
Decimating samples for mesh simplification. CCCG 2001: 85-88 - [c8]Tamal K. Dey, Joachim Giesen:
Detecting undersampling in surface reconstruction. SCG 2001: 257-263 - [c7]Tamal K. Dey, Joachim Giesen, Wulue Zhao:
Robustness Issues in Surface Reconstruction. International Conference on Computational Science (1) 2001: 658-662 - [c6]Tamal K. Dey, Joachim Giesen, James Hudson:
Sample Shuffling For Quality Hierarchic Surface Meshing. IMR 2001 - [c5]Tamal K. Dey, Joachim Giesen, James Hudson:
Delaunay based shape reconstruction from large data. IEEE Symposium on Parallel and Large-Data Visualization and Graphics 2001: 19-27 - [c4]Tamal K. Dey, Joachim Giesen, Samrat Goswami, James Hudson, Rephael Wenger, Wulue Zhao:
Undersampling and Oversampling in Sample Based Shape Modeling. IEEE Visualization 2001: 83-90 - 2000
- [j1]Joachim Giesen:
Curve Reconstruction, the Traveling Salesman Problem, and Menger's Theorem on Length. Discret. Comput. Geom. 24(4): 577-603 (2000) - [c3]Udo Adamy, Joachim Giesen, Matthias John:
New techniques for topologically correct surface reconstruction. IEEE Visualization 2000: 373-380 - [i1]Udo Adamy, Joachim Giesen, Matthias John:
The Lambda-Complex and Surface Reconstruction. EuroCG 2000: 14-17
1990 – 1999
Coauthor Index
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