Interactive simulation of surgical needle insertion and steering. - Nuttapong Chentanez; Ron Alterovitz; Daniel Ritchie; Lita Cho; Kris K. Hauser; Kenneth Y. Goldberg; Jonathan Richard Shewchuk; James F. O'Brien (ACM Trans. Graph., 2009)

Dynamic local remeshing for elastoplastic simulation. - Martin Wicke; Daniel Ritchie; Bryan Matthew Klingner; Sebastian Burke; Jonathan Richard Shewchuk; James F. O'Brien (ACM Trans. Graph., 2010)

d.tour: style-based exploration of design example galleries. - Daniel Ritchie; Ankita Arvind Kejriwal; Scott R. Klemmer (UIST, 2011)

Example-based synthesis of 3D object arrangements. - Matthew Fisher; Daniel Ritchie; Manolis Savva; Thomas A. Funkhouser; Pat Hanrahan (ACM Trans. Graph., 2012)

Probabilistic color-by-numbers: suggesting pattern colorizations using factor graphs. - Sharon Lin; Daniel Ritchie; Matthew Fisher; Pat Hanrahan (ACM Trans. Graph., 2013)

First-class runtime generation of high-performance types using exotypes. - Zachary DeVito; Daniel Ritchie; Matthew Fisher; Alex Aiken; Pat Hanrahan (PLDI, 2014)

Generating Design Suggestions under Tight Constraints with Gradient-based Probabilistic Programming. - Daniel Ritchie; Sharon Lin; Noah D. Goodman; Pat Hanrahan (Comput. Graph. Forum, 2015)

Controlling procedural modeling programs with stochastically-ordered sequential Monte Carlo. - Daniel Ritchie; Ben Mildenhall; Noah D. Goodman; Pat Hanrahan (ACM Trans. Graph., 2015)

C3: Lightweight Incrementalized MCMC for Probabilistic Programs using Continuations and Callsite Caching. - Daniel Ritchie; Andreas Stuhlmüller; Noah D. Goodman (AISTATS, 2016)

Neurally-Guided Procedural Models: Amortized Inference for Procedural Graphics Programs using Neural Networks. - Daniel Ritchie; Anna Thomas; Pat Hanrahan; Noah D. Goodman (NIPS, 2016)

Deep Amortized Inference for Probabilistic Programs. - Daniel Ritchie; Paul Horsfall; Noah D. Goodman (CoRR, 2016)

Neurally-Guided Procedural Models: Learning to Guide Procedural Models with Deep Neural Networks. - Daniel Ritchie; Anna Thomas; Pat Hanrahan; Noah D. Goodman (CoRR, 2016)

Probabilistic programming for procedural modeling and design. - Daniel Ritchie (2016)

An Improved Training Procedure for Neural Autoregressive Data Completion. - Maxime Voisin; Daniel Ritchie (CoRR, 2017)

ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans. - Angela Dai; Daniel Ritchie; Martin Bokeloh; Scott Reed; Jürgen Sturm; Matthias Nießner (CVPR, 2018)

Improving Shape Deformation in Unsupervised Image-to-Image Translation. - Aaron Gokaslan; Vivek Ramanujan; Daniel Ritchie; Kwang In Kim; James Tompkin 001 (ECCV (12), 2018)

Learning to Infer Graphics Programs from Hand-Drawn Images. - Kevin Ellis; Daniel Ritchie; Armando Solar-Lezama; Josh Tenenbaum 001 (NeurIPS, 2018)

Example-based Authoring of Procedural Modeling Programs with Structural and Continuous Variability. - Daniel Ritchie; Sarah Jobalia; Anna Thomas (Comput. Graph. Forum, 2018)

Deep convolutional priors for indoor scene synthesis. - Kai Wang 002; Manolis Savva; Angel X. Chang; Daniel Ritchie (ACM Trans. Graph., 2018)

Fast and Flexible Indoor Scene Synthesis via Deep Convolutional Generative Models. - Daniel Ritchie; Kai Wang 002; Yu-An Lin (CVPR, 2019)

Learning Generative Models of 3D Structures. - Siddhartha Chaudhuri; Daniel Ritchie; Kai Xu 004; Hao (Richard) Zhang (Eurographics (Tutorials), 2019)

Learning to Describe Scenes with Programs. - Yunchao Liu; Zheng Wu; Daniel Ritchie; William T. Freeman; Joshua B. Tenenbaum; Jiajun Wu 001 (ICLR (Poster), 2019)

Learning Style Compatibility Between Objects in a Real-World 3D Asset Database. - Yifan Liu; Ruolan Tang; Daniel Ritchie (Comput. Graph. Forum, 2019)

PlanIT: planning and instantiating indoor scenes with relation graph and spatial prior networks. - Kai Wang 002; Yu-An Lin; Ben Weissmann; Manolis Savva; Angel X. Chang; Daniel Ritchie (ACM Trans. Graph., 2019)

Shape from Tracing: Towards Reconstructing 3D Object Geometry and SVBRDF Material from Images via Differentiable Path Tracing. - Purvi Goel; Loudon Cohen; James Guesman; Vikas Thamizharasan; James Tompkin 001; Daniel Ritchie (3DV, 2020)

Motion Annotation Programs: A Scalable Approach to Annotating Kinematic Articulations in Large 3D Shape Collections. - Xianghao Xu; David Charatan; Sonia Raychaudhuri; Hanxiao Jiang 001; Mae Heitmann; Vladimir G. Kim; Siddhartha Chaudhuri; Manolis Savva; Angel X. Chang; Daniel Ritchie (3DV, 2020)

GANHopper: Multi-hop GAN for Unsupervised Image-to-Image Translation. - Wallace P. Lira; Johannes Merz; Daniel Ritchie; Daniel Cohen-Or; Hao (Richard) Zhang (ECCV (26), 2020)

Learning Generative Models of 3D Structures. - Siddhartha Chaudhuri; Daniel Ritchie; Jiajun Wu 001; Kai Xu 004; Hao (Richard) Zhang (Comput. Graph. Forum, 2020)

Learning to Infer Shape Programs Using Latent Execution Self Training. - Homer Walke; R. Kenny Jones; Daniel Ritchie (CoRR, 2020)

ShapeAssembly: learning to generate programs for 3D shape structure synthesis. - R. Kenny Jones; Theresa Barton; Xianghao Xu; Kai Wang 002; Ellen Jiang; Paul Guerrero 001; Niloy J. Mitra; Daniel Ritchie (ACM Trans. Graph., 2020)

Inferring CAD Modeling Sequences Using Zone Graphs. - Xianghao Xu; Wenzhe Peng; Chin-Yi Cheng; Karl D. D. Willis; Daniel Ritchie (CVPR, 2021)

Roominoes: Generating Novel 3D Floor Plans From Existing 3D Rooms. - Kai Wang 002; Xianghao Xu; Leon Lei; Selena Ling; Natalie Lindsay; Angel X. Chang; Manolis Savva; Daniel Ritchie (Comput. Graph. Forum, 2021)

The Neurally-Guided Shape Parser: A Monte Carlo Method for Hierarchical Labeling of Over-segmented 3D Shapes. - R. Kenny Jones; Rana Hanocka; Daniel Ritchie (CoRR, 2021)

Learning Body-Aware 3D Shape Generative Models. - Bryce Blinn; Alexander Ding; Daniel Ritchie; R. Kenny Jones; Srinath Sridhar 002; Manolis Savva (CoRR, 2021)

ShapeMOD: macro operation discovery for 3D shape programs. - R. Kenny Jones; David Charatan; Paul Guerrero 001; Niloy J. Mitra; Daniel Ritchie (ACM Trans. Graph., 2021)

Fantastic Questions and Where to Find Them: FairytaleQA - An Authentic Dataset for Narrative Comprehension. - Ying Xu; Dakuo Wang; Mo Yu; Daniel Ritchie; Bingsheng Yao; Tongshuang Wu; Zheng Zhang 043; Toby Jia-Jun Li; Nora Bradford; Branda Sun; Tran Bao Hoang; Yisi Sang; et al. (ACL (1), 2022)

StoryBuddy: A Human-AI Collaborative Chatbot for Parent-Child Interactive Storytelling with Flexible Parental Involvement. - Zheng Zhang 043; Ying Xu; Yanhao Wang; Bingsheng Yao; Daniel Ritchie; Tongshuang Wu; Mo Yu; Dakuo Wang; Toby Jia-Jun Li (CHI, 2022)

The Neurally-Guided Shape Parser: Grammar-based Labeling of 3D Shape Regions with Approximate Inference. - R. Kenny Jones; Aalia Habib; Rana Hanocka; Daniel Ritchie (CVPR, 2022)

PLAD: Learning to Infer Shape Programs with Pseudo-Labels and Approximate Distributions. - R. Kenny Jones; Homer Walke; Daniel Ritchie (CVPR, 2022)

The Shape Part Slot Machine: Contact-Based Reasoning for Generating 3D Shapes from Parts. - Kai Wang 002; Paul Guerrero 001; Vladimir G. Kim; Siddhartha Chaudhuri; Minhyuk Sung; Daniel Ritchie (ECCV (3), 2022)

Learning to Infer Kinematic Hierarchies for Novel Object Instances. - Hameed Abdul-Rashid; Miles Freeman; Ben Abbatematteo; George Konidaris 001; Daniel Ritchie (ICRA, 2022)

ShapeCrafter: A Recursive Text-Conditioned 3D Shape Generation Model. - Rao Fu; Xiao Zhan; Yiwen Chen; Daniel Ritchie; Srinath Sridhar 002 (NeurIPS, 2022)

Unsupervised Kinematic Motion Detection for Part-segmented 3D Shape Collections. - Xianghao Xu; Yifan Ruan; Srinath Sridhar 002; Daniel Ritchie (SIGGRAPH (Conference Paper Track), 2022)

TextCraft: Zero-Shot Generation of High-Fidelity and Diverse Shapes from Text. - Aditya Sanghi; Rao Fu; Vivian Liu; Karl D. D. Willis; Hooman Shayani; Amir Hosein Khasahmadi; Srinath Sridhar 002; Daniel Ritchie (CoRR, 2022)

SHRED: 3D Shape Region Decomposition with Learned Local Operations. - R. Kenny Jones; Aalia Habib; Daniel Ritchie (ACM Trans. Graph., 2022)

CLIP-Sculptor: Zero-Shot Generation of High-Fidelity and Diverse Shapes from Natural Language. - Aditya Sanghi; Rao Fu; Vivian Liu; Karl D. D. Willis; Hooman Shayani; Amir Hosein Khasahmadi; Srinath Sridhar 002; Daniel Ritchie (CVPR, 2023)

Unsupervised 3D Shape Reconstruction by Part Retrieval and Assembly. - Xianghao Xu; Paul Guerrero 001; Matthew Fisher; Siddhartha Chaudhuri; Daniel Ritchie (CVPR, 2023)

Improving Unsupervised Visual Program Inference with Code Rewriting Families. - Aditya Ganeshan; R. Kenny Jones; Daniel Ritchie (ICCV, 2023)

Explorable Mesh Deformation Subspaces from Unstructured 3D Generative Models. - Arman Maesumi; Paul Guerrero 001; Noam Aigerman; Vladimir G. Kim; Matthew Fisher; Siddhartha Chaudhuri; Daniel Ritchie (SIGGRAPH Asia, 2023)

Explorable Mesh Deformation Subspaces from Unstructured Generative Models. - Arman Maesumi; Paul Guerrero 001; Vladimir G. Kim; Matthew Fisher; Siddhartha Chaudhuri; Noam Aigerman; Daniel Ritchie (CoRR, 2023)

Neurosymbolic Models for Computer Graphics. - Daniel Ritchie; Paul Guerrero 001; R. Kenny Jones; Niloy J. Mitra; Adriana Schulz; Karl D. D. Willis; Jiajun Wu 001 (Comput. Graph. Forum, 2023)

ShapeCoder: Discovering Abstractions for Visual Programs from Unstructured Primitives. - R. Kenny Jones; Paul Guerrero 001; Niloy J. Mitra; Daniel Ritchie (ACM Trans. Graph., 2023)

Editing Motion Graphics Video via Motion Vectorization and Transformation. - Sharon Zhang; Jiaju Ma; Jiajun Wu 001; Daniel Ritchie; Maneesh Agrawala (ACM Trans. Graph., 2023)

Generalizing Single-View 3D Shape Retrieval to Occlusions and Unseen Objects. - Qirui Wu; Daniel Ritchie; Manolis Savva; Angel X. Chang (3DV, 2024)

R3DS: Reality-Linked 3D Scenes for Panoramic Scene Understanding. - Qirui Wu; Sonia Raychaudhuri; Daniel Ritchie; Manolis Savva; Angel X. Chang (ECCV (63), 2024)

Learning to Infer Generative Template Programs for Visual Concepts. - R. Kenny Jones; Siddhartha Chaudhuri; Daniel Ritchie (ICML, 2024)

Learning to Edit Visual Programs with Self-Supervision. - R. Kenny Jones; Renhao Zhang; Aditya Ganeshan; Daniel Ritchie (NeurIPS, 2024)

Can AI provide useful holistic essay scoring? - Tamara P. Tate; Jacob Steiss; Drew Bailey; Steve Graham; Youngsun Moon; Daniel Ritchie; Waverly Tseng; Mark Warschauer (Comput. Educ. Artif. Intell., 2024)

Open-Universe Indoor Scene Generation using LLM Program Synthesis and Uncurated Object Databases. - Rio Aguina-Kang; Maxim Gumin; Do Heon Han; Stewart Morris; Seung Jean Yoo; Aditya Ganeshan; R. Kenny Jones; Qiuhong Anna Wei; Kailiang Fu; Daniel Ritchie (CoRR, 2024)

Creating Language-driven Spatial Variations of Icon Images. - Xianghao Xu; Aditya Ganeshan; Karl D. D. Willis; Yewen Pu; Daniel Ritchie (CoRR, 2024)

CLIPtortionist: Zero-shot Text-driven Deformation for Manufactured 3D Shapes. - Xianghao Xu; Srinath Sridhar 002; Daniel Ritchie (CoRR, 2024)

Diorama: Unleashing Zero-shot Single-view 3D Scene Modeling. - Qirui Wu; Denys Iliash; Daniel Ritchie; Manolis Savva; Angel X. Chang (CoRR, 2024)

PossibleImpossibles: Exploratory Procedural Design of Impossible Structures. - Yuanbo Li; Tianyi Ma; Zaineb Aljumayaat; Daniel Ritchie (Comput. Graph. Forum, 2024)

CharacterMixer: Rig-Aware Interpolation of 3D Characters. - Xiao Zhan; Rao Fu; Daniel Ritchie (Comput. Graph. Forum, 2024)

One Noise to Rule Them All: Learning a Unified Model of Spatially-Varying Noise Patterns. - Arman Maesumi; Dylan Hu; Krishi Saripalli; Vladimir G. Kim; Matthew Fisher; Sören Pirk; Daniel Ritchie (ACM Trans. Graph., 2024)

ParSEL: Parameterized Shape Editing with Language. - Aditya Ganeshan; Ryan Y. Huang; Xianghao Xu; R. Kenny Jones; Daniel Ritchie (ACM Trans. Graph., 2024)

Supporting Middle School English Teachers' AI Literacy Goals Through a Generative AI Tutor. - Daniel Ritchie; Tamara P. Tate; Yi Zhang; Kristi Werry; Mark Warschauer (AIED (6), 2025)

GigaHands: A Massive Annotated Dataset of Bimanual Hand Activities. - Rao Fu; Dingxi Zhang; Alex Jiang; Wanjia Fu; Austin Funk; Daniel Ritchie; Srinath Sridhar 002 (CVPR, 2025)

Pattern Analogies: Learning to Perform Programmatic Image Edits by Analogy. - Aditya Ganeshan; Thibault Groueix; Paul Guerrero 001; Radomír Mech; Matthew Fisher; Daniel Ritchie (CVPR, 2025)

ProcTex: Consistent and Interactive Text-to-texture Synthesis for Procedural Models. - Ruiqi Xu; Zihan Zhu; Xianghao Xu; Srinath Sridhar 002; Daniel Ritchie (CoRR, 2025)

ShapeLib: designing a library of procedural 3D shape abstractions with Large Language Models. - R. Kenny Jones; Paul Guerrero 001; Niloy J. Mitra; Daniel Ritchie (CoRR, 2025)

Learning Object Placement Programs for Indoor Scene Synthesis with Iterative Self Training. - Adrian Chang; Kai Wang 002; Yuanbo Li; Manolis Savva; Angel X. Chang; Daniel Ritchie (CoRR, 2025)

Imperative vs. Declarative Programming Paradigms for Open-Universe Scene Generation. - Maxim Gumin; Do Heon Han; Seung Jean Yoo; Aditya Ganeshan; R. Kenny Jones; Rio Aguina-Kang; Stewart Morris; Daniel Ritchie (CoRR, 2025)

PartComposer: Learning and Composing Part-Level Concepts from Single-Image Examples. - Junyu Liu; R. Kenny Jones; Daniel Ritchie (CoRR, 2025)

GenHSI: Controllable Generation of Human-Scene Interaction Videos. - Zekun Li; Rui Zhou; Rahul Sajnani; Xiaoyan Cong; Daniel Ritchie; Srinath Sridhar 002 (CoRR, 2025)

Incorporating generative AI into a writing-intensive undergraduate course without off-loading learning. - Tamara P. Tate; Beth Harnick-Shapiro; Daniel Ritchie; Waverly Tseng; Michael Dennin; Mark Warschauer (Discov. Comput., 2025)