The Real Conflict Between Science and Religion: Alvin Plantinga’s Ignoratio Elenchi

By focussing on the logical relations between scientific theories and religious beliefs in his book Where the Conflict Really Lies, Alvin Plantinga overlooks the real conflict between science and religion. This conflict exists whenever religious believers endorse positive factual claims to truth concerning the supernatural. They thereby violate an important rule of scientific method and of common sense, according to which factual claims should be endorsed as true only if they result from validated epistemic methods or sources

Task-demands can immediately reverse the effects of sensory-driven saliency in complex visual stimuli

In natural vision both stimulus features and task-demands affect an observer's attention. However, the relationship between sensory-driven (“bottom-up”) and task-dependent (“top-down”) factors remains controversial: Can task-demands counteract strong sensory signals fully, quickly, and irrespective of bottom-up features? To measure attention under naturalistic conditions, we recorded eye-movements in human observers, while they viewed photographs of outdoor scenes. In the first experiment, smooth modulations of contrast biased the stimuli's sensory-driven saliency towards one side. In free-viewing, observers' eye-positions were immediately biased toward the high-contrast, i.e., high-saliency, side. However, this sensory-driven bias disappeared entirely when observers searched for a bull's-eye target embedded with equal probability to either side of the stimulus. When the target always occurred in the low-contrast side, observers' eye-positions were immediately biased towards this low-saliency side, i.e., the sensory-driven bias reversed. Hence, task-demands do not only override sensory-driven saliency but also actively countermand it. In a second experiment, a 5-Hz flicker replaced the contrast gradient. Whereas the bias was less persistent in free viewing, the overriding and reversal took longer to deploy. Hence, insufficient sensory-driven saliency cannot account for the bias reversal. In a third experiment, subjects searched for a spot of locally increased contrast (“oddity”) instead of the bull's-eye (“template”). In contrast to the other conditions, a slight sensory-driven free-viewing bias prevails in this condition. In a fourth experiment, we demonstrate that at known locations template targets are detected faster than oddity targets, suggesting that the former induce a stronger top-down drive when used as search targets. Taken together, task-demands can override sensory-driven saliency in complex visual stimuli almost immediately, and the extent of overriding depends on the search target and the overridden feature, but not on the latter's free-viewing saliency

A^2-Net: Molecular Structure Estimation from Cryo-EM Density Volumes

Constructing of molecular structural models from Cryo-Electron Microscopy (Cryo-EM) density volumes is the critical last step of structure determination by Cryo-EM technologies. Methods have evolved from manual construction by structural biologists to perform 6D translation-rotation searching, which is extremely compute-intensive. In this paper, we propose a learning-based method and formulate this problem as a vision-inspired 3D detection and pose estimation task. We develop a deep learning framework for amino acid determination in a 3D Cryo-EM density volume. We also design a sequence-guided Monte Carlo Tree Search (MCTS) to thread over the candidate amino acids to form the molecular structure. This framework achieves 91% coverage on our newly proposed dataset and takes only a few minutes for a typical structure with a thousand amino acids. Our method is hundreds of times faster and several times more accurate than existing automated solutions without any human intervention.Comment: 8 pages, 5 figures, 4 table

Online, interactive user guidance for high-dimensional, constrained motion planning

We consider the problem of planning a collision-free path for a high-dimensional robot. Specifically, we suggest a planning framework where a motion-planning algorithm can obtain guidance from a user. In contrast to existing approaches that try to speed up planning by incorporating experiences or demonstrations ahead of planning, we suggest to seek user guidance only when the planner identifies that it ceases to make significant progress towards the goal. Guidance is provided in the form of an intermediate configuration $\hat{q}$, which is used to bias the planner to go through $\hat{q}$. We demonstrate our approach for the case where the planning algorithm is Multi-Heuristic A* (MHA*) and the robot is a 34-DOF humanoid. We show that our approach allows to compute highly-constrained paths with little domain knowledge. Without our approach, solving such problems requires carefully-crafting domain-dependent heuristics

Online, interactive user guidance for high-dimensional, constrained motion planning

We consider the problem of planning a collision-free path for a high-dimensional robot. Specifically, we suggest a planning framework where a motion-planning algorithm can obtain guidance from a user. In contrast to existing approaches that try to speed up planning by incorporating experiences or demonstrations ahead of planning, we suggest to seek user guidance only when the planner identifies that it ceases to make significant progress towards the goal. Guidance is provided in the form of an intermediate configuration $\hat{q}$, which is used to bias the planner to go through $\hat{q}$. We demonstrate our approach for the case where the planning algorithm is Multi-Heuristic A* (MHA*) and the robot is a 34-DOF humanoid. We show that our approach allows to compute highly-constrained paths with little domain knowledge. Without our approach, solving such problems requires carefully-crafting domain-dependent heuristics

In Search of Intuition

What are intuitions? Stereotypical examples may suggest that they are the results of common intellectual reflexes. But some intuitions defy the stereotype: there are hard-won intuitions that take d..