Deep learning-enabled medical computer vision
A decade of unprecedented progress in artificial intelligence (AI) has demonstrated the
potential for many fields—including medicine—to benefit from the insights that AI techniques …
potential for many fields—including medicine—to benefit from the insights that AI techniques …
Coderl: Mastering code generation through pretrained models and deep reinforcement learning
Program synthesis or code generation aims to generate a program that satisfies a problem
specification. Recent approaches using large-scale pretrained language models (LMs) have …
specification. Recent approaches using large-scale pretrained language models (LMs) have …
Scene representation networks: Continuous 3d-structure-aware neural scene representations
Unsupervised learning with generative models has the potential of discovering rich
representations of 3D scenes. While geometric deep learning has explored 3D-structure …
representations of 3D scenes. While geometric deep learning has explored 3D-structure …
Shapeassembly: Learning to generate programs for 3d shape structure synthesis
Manually authoring 3D shapes is difficult and time consuming; generative models of 3D
shapes offer compelling alternatives. Procedural representations are one such possibility …
shapes offer compelling alternatives. Procedural representations are one such possibility …
Learning to synthesize programs as interpretable and generalizable policies
Recently, deep reinforcement learning (DRL) methods have achieved impressive
performance on tasks in a variety of domains. However, neural network policies produced …
performance on tasks in a variety of domains. However, neural network policies produced …
Learning to infer and execute 3d shape programs
Human perception of 3D shapes goes beyond reconstructing them as a set of points or a
composition of geometric primitives: we also effortlessly understand higher-level shape …
composition of geometric primitives: we also effortlessly understand higher-level shape …
Learning unsupervised hierarchical part decomposition of 3d objects from a single rgb image
Humans perceive the 3D world as a set of distinct objects that are characterized by various
low-level (geometry, reflectance) and high-level (connectivity, adjacency, symmetry) …
low-level (geometry, reflectance) and high-level (connectivity, adjacency, symmetry) …
Outline, then details: Syntactically guided coarse-to-fine code generation
For a complicated algorithm, its implementation by a human programmer usually starts with
outlining a rough control flow followed by iterative enrichments, eventually yielding carefully …
outlining a rough control flow followed by iterative enrichments, eventually yielding carefully …
Symbol-LLM: leverage language models for symbolic system in visual human activity reasoning
Human reasoning can be understood as a cooperation between the intuitive, associative"
System-1''and the deliberative, logical" System-2''. For existing System-1-like methods in …
System-1''and the deliberative, logical" System-2''. For existing System-1-like methods in …
Proto: Program-guided transformer for program-guided tasks
Programs, consisting of semantic and structural information, play an important role in the
communication between humans and agents. Towards learning general program executors …
communication between humans and agents. Towards learning general program executors …